Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Multi-objective optimization for eco-efficient food supply chains
Banasik, Aleksander - \ 2017
University. Promotor(en): Jacqueline Bloemhof-Ruwaard; Jack van der Vorst, co-promotor(en): Frits Claassen. - Wageningen : Wageningen University - ISBN 9789463430944 - 147
food chains - supply chain management - food production - mushrooms - decision support systems - production planning - models - voedselketens - ketenmanagement - voedselproductie - paddestoelen - beslissingsondersteunende systemen - productieplanning - modellen

Until recently, food production focused mainly on delivering high-quality products at low cost and little attention was paid to environmental impact and depletion of natural resources. As a result of the growing awareness of climate change, shrinking resources, and increasing world population, this trend is changing. A major concern in Food Supply Chains (FSCs) is food waste. To remain competitive, FSCs are challenged to adopt new technologies that reduce or valorize food waste. These technologies can contribute to maintaining or increasing economic output and concurrently reduce the environmental impact of current operations, i.e. achieving what has been defined as eco-efficiency. Designing eco-efficient supply chains requires complex decision support models that can deal with multiple dimensions of sustainability while taking into account the specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM), a research field within Operations Research, is particularly suitable to support decision making when multiple and (mostly) conflicting criteria are involved. In this research, multi-objective optimization was used to quantify trade-offs between conflicting objectives and derive eco-efficient solutions, i.e. solutions in which environmental performance can only be improved at higher cost. The overall objective of this thesis was to support decision making in FSCs by developing dedicated decision support models to optimize and re-design FSCs by balancing the economic and environmental criteria. The emphasis is directed towards valorization of product flows by means of closing loops and waste management at a chain level. In line with this overall objective, four research questions were defined, which are addressed in Chapters 2 to 5.

In Chapter 2, the use of MCDM approaches for designing Green Supply Chains (GSCs) is reviewed; GSCs extend traditional supply chains to include activities that minimize the environmental impact of a product throughout its life cycle. A conceptual framework was developed to find relevant publications and categorize papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that the use of MCDM approaches for designing GSCs is a new but emerging research field. Most publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations. Most papers assume all data to be deterministic. Moreover, little attention has been given to minimization of waste in studies on FSCs, and numerous indicators are used to account for eco-efficiency, indicating the lack of standards. Chapter 2, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with respect to supply chains dealing with food production, and with inclusion of uncertainty in parameters.

Environmental concerns and scarcity of resources encourage decision makers in supply chains to consider alternative production options that include preventing the production of waste streams and simultaneously reusing and recycling waste materials. Until now, quantitative modelling approaches on closing loops in FSCs have been rare in the literature. The aim of Chapter 3 was to develop a mathematical model that can be used for quantitative assessment of alternative production options associated with different ways of dealing with waste in FSCs, i.e. prevention, recycling, and disposal of food waste. A multi-objective mixed integer linear programming model was developed to derive a set of eco-efficient solutions corresponding to production planning decisions. The environmental performance of the chain is expressed by an indicator based on exergy analysis, which has the potential to capture other commonly used indicators, such as energy consumption, fuel consumption, and waste generation, in a single value. This simplifies the calculation of the eco-efficient frontier and enables its intuitive graphical representation, which is much easier to communicate to the decision makers. The applicability of the model is demonstrated on a real-life industrial bread supply chain in the Netherlands. The results confirm the findings from the literature that prevention is the best waste management strategy from an environmental perspective. The advantages of using exergy as an indicator to capture the environmental performance is demonstrated by comparing the outcomes with other commonly used indicators of environmental performance. The potential of studying food production planning decision problems in a multi-objective context is illustrated and the applicability of the model in the assessment of alternative production options is demonstrated.

In contrast to closed-loop studies in industry involving discrete parts, in FSCs the value of the final product usually cannot be regained. However, the components used for production, such as organic matter or a growing medium, can be recycled. The aim of Chapter 4 was to reveal the consequences of closing loops in a mushroom supply chain. A multi-objective mixed integer linear programming model was proposed to quantify trade-offs between economic and environmental indicators and to explore alternative recycling technologies quantitatively. The model was developed to re-design the logistical structure and close loops in the mushroom supply chain. It was found that adopting closing loop technologies in industrial mushroom production has the potential to increase the total profitability of the chain by almost 11% and improve the environmental performance by almost 28%. It is concluded that a comprehensive evaluation of recycling technologies and re-designing logistical structures requires quantitative tools that simultaneously optimize managerial decisions at strategic and tactical levels.

Multi-objective optimization models are often developed under the assumption that all information required for model parameterization is known in advance. In practice, however, not all the required information is available in advance because of various sources of uncertainty in FSCs. In Chapter 5, a multi-objective two-stage stochastic programming model was proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in FSCs. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. It is demonstrated that taking uncertainty into account at the production planning phase in an FSC can bring substantial economic and environmental benefits.

The research presented in this thesis contributes to the scientific literature on eco-efficient FSCs by providing decision support models for use by decision makers to assess alternative logistical structures and quantify the economic and environmental implications of closing loop technologies. This thesis shows that technological innovations, which allow for reuse and recycling of waste streams, have the potential to improve the economic and environmental performance of an FSC substantially. The case studies illustrate that it is worthwhile investing in research on technological innovations (and their development) for closing loops in FSCs. The greatest benefits are brought about by using materials to their full potential by valorizing waste streams as much as possible.

Assessing biodiversity change in scenario studies : introducing a decision support tool for analysing the impact of nature policy
Pouwels, Rogier ; Bilt, Willem van der; Hinsberg, Arjen van; Knegt, Bart de; Reijnen, Rien ; Verboom, Jana ; Jones-Walters, Lawrence - \ 2016
Wageningen : Wettelijke Onderzoekstaken Natuur & Milieu (WOt-paper 39) - 16
biodiversity - policy - decision support systems - habitats - ecosystems - biodiversiteit - beleid - beslissingsondersteunende systemen - ecosystemen
Biodiversity conservation is firmly established on the
political agenda. Nested goals and targets for biodiversity
have therefore been formulated and agreed at global,
regional, national and sub-national levels in order to halt
and reverse its decline. In order to measure progress in
relation to the delivery of such targets, policymakers have
a range of tools and indicators that allow them to monitor
and evaluate the effect of their policies, instruments and
associated actions. In terms of the policy cycle, evaluation
should result in the further modification and refinement of
policy instruments towards improved delivery in the
future.
Beheersing emissie grondgebonden kasteelten
Voogt, W. ; Balendonck, J. ; Janse, J. ; Swinkels, G.L.A.M. ; Winkel, A. van - \ 2015
Bleiswijk : Wageningen UR Glastuinbouw (Rapport GTB 1363) - 38
teelt onder bescherming - snijbloemen - emissie - beslissingsondersteunende systemen - biologische landbouw - irrigatie - lysimeters - sensors - water - voedingsstoffenbalans - voedingsstoffen - optimalisatie - protected cultivation - cut flowers - emission - decision support systems - organic farming - irrigation - nutrient balance - nutrients - optimization
To make growers to be in control of the emission, a decision support system is developed for irrigation in soil grown crops. In 2013-2014 the implementation was continued and several greenhouse crops were monitored. As was found earlier, the organic greenhouse growers are able to control irrigation in a way that emission is reduced to a minimum. The results obtained at (conventional) flower growers show sometimes high emission of nitrogen. This is due at one hand to high irrigation surpluses but also to high fertilisation of nitrogen. Better tuning of the water- and nitrogen supply to the crop demand is necessary. For these stapes growers need better soil-moisture sensors.
Prototype van een Dynamisch Input Advies Systeem voor biogasinstallaties
Timmerman, M. ; Riel, J.W. van - \ 2015
Wageningen : Wageningen UR Livestock Research (Livestock Research rapport 897) - 58
bio-energie - biogas - gasproductie - co-vergisting - mestvergisting - beslissingsondersteunende systemen - optimalisatie - energieproductie in de landbouw - melkveehouderij - biobased economy - bioenergy - gas production - co-fermentation - manure fermentation - decision support systems - optimization - agricultural energy production - dairy farming
Het Dynamisch Input Advies Systeem (Dynamisch Vergisten) voor biogasinstallaties maakt gebruik van bedrijfsspecifieke procesgegevens voor de dagelijkse bijsturing van de input naar een biogasinstallatie. Het adviessysteem bestaat uit een methodiek die dagelijks de actuele invloed bepaalt van de input op de biogasproductie en een control algoritme die op basis van de relatie tussen de input en de biogasproductie de optimale input bepaalt. Op basis hiervan wordt de input bijgesteld in de richting van de optimale input. Het control algoritme kan worden ingesteld om de input voor de maximaal haalbare biogasproductie te bepalen of om de input te bepalen waarbij het voersaldo (energieopbrengst minus voerkosten) maximaal is. Het doel van het onderzoek was het vaststellen van het “proof of principle” van de methodiek van Dynamisch Vergisten onder praktijkomstandigheden. Het onderzoek heeft plaatsgevonden op een melkveeproefbedrijf en een praktijkbedrijf. Uit de resultaten blijkt dat het principe van Dynamisch Vergisten in staat was om de input zo te sturen dat de biogasproductie toe nam zonder dat het vergistingsproces nadelig werd beïnvloed. De toename in biogasproductie leidde tot hogere voersaldo’s. De methodiek van Dynamisch Vergisten biedt perspectief om het financiële rendement van biogasinstallaties te verbeteren.
Decision-making guidance for pesticide registration : pesticide risk reduction programme - Ethiopia
Valk, H. van der; Vliet, P. van; Peeters, F.M. - \ 2015
Alterra Wageningen UR : Wageningen (Alterra-report 2659) - 39
pesticiden - toelating van bestrijdingsmiddelen - registratie - besluitvorming - beslissingsondersteunende systemen - risicovermindering - ethiopië - pesticides - authorisation of pesticides - registration - decision making - decision support systems - risk reduction - ethiopia
Decision support modeling for sustainable food logistics management
Soysal, M. - \ 2015
University. Promotor(en): Jack van der Vorst, co-promotor(en): Jacqueline Bloemhof-Ruwaard. - Wageningen : Wageningen University - ISBN 9789462573055 - 209
logistiek - voedsel - voedselketens - voedselproducten - duurzaamheid (sustainability) - ketenmanagement - beslissingsondersteunende systemen - kwantitatieve analyse - voedselafval - energiegebruik - modelleren - logistics - food - food chains - food products - sustainability - supply chain management - decision support systems - quantitative analysis - food wastes - energy consumption - modeling

Summary

For the last two decades, food logistics systems have seen the transition from traditional Logistics Management (LM) to Food Logistics Management (FLM), and successively, to Sustainable Food Logistics Management (SFLM). Accordingly, food industry has been subject to the recent challenges of reducing the amount of food waste and raising energy efficiency to reduce greenhouse gas emissions. These additional challenges add to the complexity of logistics operations and require advanced decision support models which can be used by decision makers to develop more sustainable food logistics systems in practice. Hence, the overall objective of this thesis was to obtain insight in how to improve the sustainability performance of food logistics systems by developing decision support models that can address the concerns for transportation energy use and consequently carbon emissions, and/or product waste, while also adhering to competitiveness. In line with this overall objective, we have defined five research objectives.

The first research objective (RO), which is to identify key logistical aims, analyse available quantitative models and point out modelling challenges in SFLM, is investigated in Chapter 2. In this chapter, key logistical aims in LM, FLM and SFLM phases are identified, and available quantitative models are analysed to point out modelling challenges in SFLM. A literature review on quantitative studies is conducted and also qualitative studies are consulted to better understand the key logistical aims and to identify the relevant system scope issues. The main findings of the literature review indicate that (i) most studies rely on a completely deterministic environment, (ii) the food waste challenge in logistics has not received sufficient attention, (iii) traveled distance is often used as a single indicator to estimate related transportation cost and emissions, and (iv) most studies propose single objective models for the food logistics problems. This chapter concludes that new and advanced quantitative models are needed that take specific SFLM requirements from practice into consideration to support business decisions and capture food supply chain dynamics. These findings motivated us to work on the following research objectives RO2, RO3, RO4 and RO5.

RO2, which is to analyse the relationship between economic (cost) and environmental (transportation carbon emissions) performance in a network problem of a perishable product, is investigated in Chapter 3. This chapter presents a multi-objective linear programming (MOLP) model for a generic beef logistics network problem. The objectives of the model are (i) minimizing total logistics cost and (ii) minimizing total amount of greenhouse gas emissions from transportation operations. The model is solved using the e-constraint method. This study breaks away from the literature on logistics network models by simultaneously considering transportation emissions (affected by road structure, vehicle and fuel types, weight loads of vehicles, traveled distances), return hauls and product perishability in a MOLP model. We present computational results and analyses based on the application of the model to a real-life international beef logistics chain operating in Nova Andradina, Mato Grosso do Sul, Brazil, and exporting beef to the European Union. Trade-off relationships between multiple objectives are observed by the derived Pareto frontier that presents the cost of being sustainable from the point of reducing transportation emissions. The results indicate the importance of distances between actors in terms of environmental impact. Moreover, sensitivity analysis on important practical parameters show that export ports' capacities put pressure on the logistics system; decreasing fuel efficiency due to the bad infrastructure has negative effects on cost and emissions; and green tax incentives result in economic and environmental improvement.

RO3, which is to investigate the performance implications of accommodating explicit transportation energy use and traffic congestion concerns in a two-echelon capacitated vehicle routing problem (2E-CVRP), is investigated in Chapter 4. The multi-echelon distribution strategy in which freight is delivered to customers via intermediate depots rather than using direct shipments is an increasingly popular strategy in urban logistics. Its popularity is primarily due to the fact that it alleviates the environmental (e.g., energy usage and congestion) and social (e.g., traffic-related air pollution, accidents and noise) consequences of logistics operations. This chapter presents a comprehensive mixed integer linear programming formulation for a time-dependent 2E-CVRP that accounts for vehicle type, traveled distance, vehicle speed, load, multiple time zones and emissions. A case study in a supermarket chain operating in the Netherlands shows the applicability of the model to a real-life problem. Several versions of the model, each differing with respect to the objective function, are tested to produce a number of selected Key Performance Indicators (KPIs) relevant to distance, time, fuel consumption and cost. This chapter offers insight in the economies of environmentally-friendly vehicle routing in two-echelon distribution systems. The results suggest that an environmentally-friendly solution is obtained from the use of a two-echelon distribution system, whereas a single-echelon distribution system provides the least-cost solution.

RO4, which is to investigate the performance implications of accommodating explicit transportation energy use, product waste and demand uncertainty concerns in an inventory routing problem (IRP), is investigated in Chapter 5. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the IRP literature restrict the usefulness of the proposed models in current food logistics systems. From this point of view, our interest in this chapter is to enhance the traditional models for the IRP to make them more useful for decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements, and thus offers better support to decision makers.

RO5, which is to analyse the benefits of horizontal collaboration in a green IRP for perishable products with demand uncertainty, is investigated in Chapter 6. This chapter presents a decision support model, which includes a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand, for the IRP with multiple suppliers and customers. The model allows to analyse the benefits of horizontal collaboration in the IRP with respect to several KPIs, i.e., total emissions, total driving time, total routing cost comprised of fuel and wage cost, total inventory cost, total waste cost, and total cost. A case study on the distribution operations of two suppliers, where the first supplier produces figs and the second supplier produces cherries, shows the applicability of the model to a real-life problem. The results show that horizontal collaboration among the suppliers contributes to the decrease of aggregated total cost and emissions in the logistics system, whereas the obtained gains are sensitive to the changes in parameters such as supplier size or maximum product shelf life. According to the experiments, the aggregated total cost benefit from cooperation varies in a range of about 4-24% and the aggregated total emission benefit varies in a range of about 8-33%.

Integrated findings from Chapters 2, 3, 4, 5 and 6 contribute to the SFLM literature by (i) reflecting the state of the art on the topic of quantitative logistic models which have sustainability considerations, (ii) providing decision support models which can be used by decision makers to improve the performance of the sustainable food logistics systems in terms of logistics cost, transportation energy use and carbon emissions, and/or product waste, and (iii) presenting the applicability of the proposed models in different case studies based on mainly real data, multiple scenarios, and analysis. The developed decision support models exploit several logistics improvement opportunities regarding transportation energy use and emissions, and/or product waste to better aid SFLM, as distinct from their counterparts in literature. To conclude, the case study implementations in this thesis demonstrate that (i) perishability and explicit consideration of fuel consumption are important aspects in logistics problems, and (ii) the provided decision support models can be used in practice by decision makers to further improve sustainability performance of the food logistics systems.

Decision Support System (DSS) for prevention of Botrytis in tomato in greenhouses
Visser, P.H.B. de; Nannes, L. ; Bokhoven, E.H. van; Buwalda, F. - \ 2015
Bleiswijk : Wageningen UR Glastuinbouw (Rapport GTB 1345) - 36
glastuinbouw - tomaten - gewasbescherming - plantenziekteverwekkende schimmels - botrytis - beslissingsondersteunende systemen - preventie - ziektebestrijdende teeltmaatregelen - klimaatregeling - teeltsystemen - greenhouse horticulture - tomatoes - plant protection - plant pathogenic fungi - decision support systems - prevention - cultural control - air conditioning - cropping systems
Within the framework of the Interreg project ‘Gezonde Kas’ a decision support system (DSS) for Botrytis risk in tomato was developed. This report fi rst summarizes existing knowledge on botrytis in tomato. The quantitative relationships are subsequently laid down in computer code. This code formed the basis of a dynamic simulation model to predict the risk on botrytis in a tomato crop. The model requires input from the climate computer of the greenhouse, and can also manage input from manual measurements. The report describes when and how the model predicts a high spore pressure and an increased risk on Botrytis infection, on the basis of climate conditions in the greenhouse. The prediction is highly improved when the data from the regular measurement box (‘meetbox’) are extended with data from a grid of sensors, positioned on representative spots in the greenhouse. The use of the model is facilitated for growers by the addition of a graphical user interface (GUI). The functionality of the GUI is explained. The DSS is now commercially available for growers and advisors, and can be used with and without other products of the Gezonde Kas project
Progress Report China Potato GAP project; Late blight control, seed quality, storage facilities and sustainability studies in Heilongjiang province and communications
Kempenaar, C. ; Kessel, G.J.T. ; Wustman, R. ; Pronk, A.A. ; Haverkort, A.J. ; Ruijter, F.J. de; Lyu, D. ; Wan, S. ; Fan, G. ; Bai, Y. ; Min, F. ; Guo, M. ; Zhang, S. ; Yang, S. ; Gao, Y. - \ 2015
Wageningen : Plant Research International (Report / Plant Research International 608) - 73
potatoes - seed potatoes - solanum tuberosum - good practices - phytophthora infestans - disease resistance - decision support systems - seed quality - land use - water use efficiency - storage - storage equipment - china - aardappelen - pootaardappelen - ziekteresistentie - beslissingsondersteunende systemen - zaadkwaliteit - landgebruik - watergebruiksrendement - opslag - voorzieningen voor de opslag
In this report we describe the mid-term results of the R&D program of the PPS Potato GAP China. The aim of the Potato GAP China PPS is to exchange information on GAP in potato production and storage, and to set up experiments and demonstration farms in China with Dutch technology and know-how. This last objective, the setup of Centres of Dutch potato Expertise in China, has not been achieved yet, but still has high priority in 2015. In this report, we describe the results of experiments, investigations and communications within the PPS in 2013 and 2014. The R&D topics are potato late blight disease monitoring and control, potato seed quality evaluation, potato storage investigation and sustainability evaluation of potato production.
MCA Verondiepen: multicriteria-instrument voor locatiekeuze en inrichting bij het verondiepen van diepe plassen
Lange, H.J. de; Gylstra, R. ; Huijsmans, T. ; Nusselein, T. ; Verbeek, S. - \ 2014
veengebieden - plassen - stort - grondverzet - baggerspeciedepots - beslissingsondersteunende systemen - peatlands - ponds - spoil - earth moving - spoil banks - decision support systems
Het nuttig toepassen van grond of baggerspecie kan als kans worden gezien in gebiedsontwikkeling of natuurontwikkeling in en rond een diepe plas. Om een optimale keuze voor inrichting en functie te kunnen maken, moeten verschillende aspecten worden afgewogen. Hiervoor is de MCA Verondiepen ontwikkeld, een multicriteria-instrument om stakeholders op een gestructureerde wijze mee te laten denken over de huidige functie en kwaliteit, impact van herinrichting, en mogelijke nieuwe functie en kwaliteit. De toepassing van de MCA Verondiepen wordt geïllustreerd aan de hand van vijf praktijkvoorbeelden.
Sporulatie en beheersing echte meeldauw in aardbei : bouwstenen voor beslissing ondersteunend systeem (BOS) voor de beheersing van meeldauw in aardbei
Evenhuis, A. ; Topper, C.G. ; Wilms, J.A.M. - \ 2014
Wageningen : Praktijkonderzoek Plant & Omgeving, Business Unit AGV - 47
aardbeien - fragaria ananassa - gewasbescherming - meeldauw - beslissingsondersteunende systemen - vruchtrot - teeltsystemen - alternatieve methoden - fungiciden - sporulatie - biologische processen - strawberries - plant protection - mildews - decision support systems - fruit rots - cropping systems - alternative methods - fungicides - sporulation - biological processes
Echte meeldauw in aardbei kan zowel het blad als de vrucht aantasten. In de praktijk wordt de schimmel bestreden door regelmatige inzet van gewasbeschermingsmiddelen. Het is gewenst om die inzet te beperken tot het noodzakelijke. Dit is zowel economisch en milieutechnisch aantrekkelijk. In het algemeen kunnen waarschuwingssystemen helpen om het tijdstip van de inzet van gewasbeschermingsmiddelen te optimaliseren. Voor echte meeldauw zijn er een aantal beslissingsondersteunende systemen (BOS) op de markt (PlantPLus van Dacom Plant service en Aardbei bericht van Agrovision). In de teelt van aardbei wordt een advies gegeven voor vruchtrot en een advies voor meeldauw. Ervaring leert dat het advies voor meeldauw toch lastig is door wisselende weersomstandigheden en daar komt nog bij de aardbeien geteeld op stellingen, al of niet met regenkapje, te maken hebben met een ander microklimaat dan aardbeien geteeld in de vollegrond. Voor meeldauw geldt dan ook nog dat de biologie van deze schimmel minder goed bekend is dan die van Botrytis cinerea (vruchtrot). Het project is er op gericht om een de biologie van echte meeldauw in aardbei verder te ontrafelen. Deze kennis kan gebruikt worden om de bestrijdingsstrategie voor echte meeldauw in aardbei te ontwikkelen, gebaseerd op de biologie van de schimmel, de weersomstandigheden en de vitaliteit van het gewas. Veel gegevens over kieming, infectie en kolonisatie van aardbeiblad zijn beschreven in de literatuur.
Optimization-based decision support systems for planning problems in processing industries
Claassen, G.D.H. - \ 2014
University. Promotor(en): Jack van der Vorst. - Wageningen : Wageningen University - ISBN 9789462572089 - 171
operationeel onderzoek - logistiek - voedselverwerking - voedselindustrie - pulp- en papierwarenindustrie - beslissingsondersteunende systemen - optimalisatie - procesoptimalisatie - wiskundige modellen - operations research - logistics - food processing - food industry - pulp and paper industry - decision support systems - optimization - process optimization - mathematical models

Summary

Optimization-based decision support systems for planning problems in processing industries

Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. The history of such systems started in 1971 when the concept of Decision Support Systems (DSS) emerged. Over the years, the field of DSS has evolved into a broad variety of directions. The described research in this thesis limits to the category of model-driven or optimization-based DSS.

Simultaneously with the emergence of DSS, software vendors recognized the high potentials of available data and developed Enterprise Systems to standardize planning problems. Meanwhile, information oriented systems like MRP and its successors are extended by the basic concepts of optimization based decision support. These systems are called Advanced Planning Systems (APS). The main focus of APS is to support decision making at different stages or phases in the material flow, i.e. from procurement, production, distribution to sales (horizontal-axis), on different hierarchical aggregation levels (vertical-axis) ranging from strategic (long-term) to operational (short- term) planning. This framework of building blocks decomposes planning tasks hierarchically into partial planning problems. This basic architecture of the planning processes in APS is known as the Supply Chain Planning Matrix (SCPM).

Compared to, for instance, discrete parts manufacturing, planning tasks are much more complicated in processing industries due to a natural variation in the composition of raw materials, the impact of processing operations on properties of material flows, sequence dependent change-over times, the inevitable decline in quality of product flows and relatively low margins. These specific characteristics gave rise to focus on optimization-based decision support in the domain of processing industries. The problems to be addressed in this field call for (inter-related) decisions with respect to the required raw materials, the production quantities to be manufactured, the efficient use of available resources, and the times at which raw materials must be available.

Although different APS modules can interact directly, coordination and integration is often restricted to the exchange of data flows between different modules. Given the need for specific integrated decision support, the research presented in this thesis focusses particularly on medium to short term decision support at production stage in processing industry, including the vertical and horizontal integration and coordination with adjacent building blocks in the SCPM.

Extensive reviews from literature show that the gap between research and practice of DSS is widening. As the field of DSS was initiated as an application oriented discipline, the strategy of what is referred to as “application-driven theory” was taken as the preferred approach for this thesis. “Application-driven” refers to a bottom-up approach which means that the relevance of the research should both be initiated and obtained from practice. The intended successful use of the proposed approaches should, where possible, be represented by tests of adequacy. Simultaneously, the contribution to “theory” aims to be a recognizable part of the research effort, i.e.

obtained understanding and insights from problems in practice should provide the basis for new approaches. Based on the preceding considerations we defined the following general research objective:

General research objective

To support medium- to short term planning problems by optimization-based models and solution techniques such that:

i) The applicability and added value of (prototype) systems is recognized and carried by decision makers in practice

ii) The proposed approaches contribute to knowledge, understanding and insights from a model building and solving point of view.

In order to link the general objective with the different studies in the thesis, we defined five, recurring research premises, i.e. Professional relevance and applicability (P1), Aggregation (P2), Decomposition and reformulation (P3), Vertical integration at production level (P4), and Horizontal coordination and integration (P5).

The overarching premise P1 refers to the first part of the research objective. All other premises refer to the second part of the research objective, i.e. model building and/or – solving. Several planning issues are studied to give substance to the research objective and each study is connected to at least two research premises.

Study 1: Planning and scheduling in food processing industry

The main question in Chapter 2 was:” How to apply aggregation, decomposition and reformulation in model-based DSS at planning and scheduling level such that the aspect of decision support is recognized and appreciated by decision makers in practice, and which level of aggregation is needed to integrate production planning (i.e. lot-sizing) and scheduling problems in a single model?

The study consists of two parts. The first part of the study refers to a case study for the bottleneck packaging facilities of a large dairy company. The goal was to develop, implement and test a pilot DSS which was able to deliver solutions recognized and carried by decision makers at lower decision levels. The latter aim implied that a straight-forward aggregation on time, product type, resources or product stage, was not preferred. The key to develop an approach for regular use was to identify and take advantage of specific problem characteristics. Clustering of numerous jobs, while retaining information at order level, could be exploited in a reformulation approach. The inclusion of (combined) generalized- and variable upper bound constraints gave very tight lower bounds and sparse search trees.

An extensive test phase in daily practice showed that the main benefit of the DSS was the initial quality of the generated plans including the time needed to generate these schedules. Hence, decision makers could i) postpone their planning tasks, ii) conveniently cope with rush orders or planned maintenance and iii) easily generate

alternatives or revised plans when unforeseen disturbances occur. Moreover, the graphical presentation and overview of the (future) working schedule enabled order acceptance to make use of remaining capacity.

The study also showed that planning problems in practice cannot be captured exhaustively by a (simplified) model. Decision makers need the opportunity to modify automatically generated plans manually and use human judgement and experience such that the solution is tuned to the actual situation. Hence, the DSS should not be considered as an optimizer but rather as a tool for generating high quality plans to be used for further analysis. Within this context the various options of a user-friendly, graphical, and fully interactive user interface, were of major importance.

Although the case study clearly demonstrates the validity of earlier case based DSS research for current days APS, the proposed approach is hardly a generic solution for a complete vertical integration between lot-sizing and scheduling. If lot-size decisions are strongly affected by the sequence of jobs, production planning and scheduling should be performed simultaneously.

As the described case refers to an earlier study and today’s APS do not provide modules for integrated lot-sizing and scheduling, the second part of the study gives an overview of developments in literature regarding lot-sizing and scheduling models and assess their suitability for addressing sequence-dependent setups, non-triangular setups and product decay. The review shows a tendency in which so-called Big Bucket (BB) models are currently proposed for short term time horizons too. However, we argue that segmentation of the planning horizon is a key issue for simultaneous lot-sizing and scheduling. The advantage of BB models may become a major obstacle for i) the effectiveness of simultaneous lot-sizing and scheduling, and ii) addressing specific characteristics in food processing industry.

Study 2: Vertical integration of lot-sizing and scheduling in food processing industry

Chapter 3 focused on a complete integration of lot-sizing and scheduling decisions in a single model. The main question was:” How to integrate production planning (i.e. lot- sizing) and scheduling problems in a single model, such that common assumptions regarding the triangular setup conditions are relaxed and issues of product decay and limited shelf lives are taken into account?”

The literature research in Chapter 2 revealed that the computational advantage of time oriented aggregation in BB models may become a major obstacle in addressing the identified characteristics in FPI. In addition, product decay is primarily associated with the “age” of products and consequently relates to the segmentation of the time- horizon. Therefore, two SB models are developed to demonstrate the impact of non- triangular setups and product decay on the generated solutions. Small scale examples were used to demonstrate how a small change in the balance between inventory - and

changeover costs may generate significantly different solutions, especially when the triangular setup conditions do not hold.

The developed models are potentially very large formulations and, as expected, hard to solve. Exploratory research was conducted with a Relax-and-Fix (R&F) heuristic. The heuristic is based on a decomposition of the time horizon. Numerical results of small to medium sized problem instances are promising. However, solving real-size problem instances is not possible yet.

Study 3: Integrated planning between procurement and production

The case study in Chapter 4 focussed on the need for horizontal coordination and integration between the phases procurement and production, which is of particular importance in inter-organizational supply chains. The main question was:” How to model and solve an integrated planning problem between procurement and production, both on a mid-term and short-term planning level, in an inter-organizational supply chain? The research question was projected on an illustrative milk collection problem in practice.

The aim was to develop a pilot DSS that lifted decision support for a “weaker” partner in a food supply chain to a higher level, and to illustrate the importance of horizontal integration between the phases procurement and production in an APS framework.

Problem analysis revealed that the problem can be classified as an extension of the Periodic Vehicle Routing Problem (PVRP). The problem was decomposed into more tractable sub problems on different hierarchical levels, i.e. the daily (vehicle) routing problem was separated from a medium-term planning problem. On the higher planning level, numerous suppliers were aggregated such that total supply within a cluster met (multiple) vehicle loading capacities. The continuous supply of relatively small amounts from many suppliers had to be balanced with strict delivery conditions at processing level. A model was developed to assign a single (stable) collection rhythm to each cluster such that the total, weighted deviation of desired processing levels on various days in the planning horizon was minimized.

The applied aggregation on the higher planning level turned out to be very beneficial for the required disaggregation at the lower planning level. Once supplier farms were geographically grouped into clusters and the aggregated supply within a cluster was assigned to a single collection rhythm with fixed collection days, the (initial) daily routing problem was considerably easier to solve for vehicle schedulers.

The computational complexity of the problem was reduced by exploiting application-based properties algorithmically in a specific branch-and-bound scheme, i.e. a customized approach of Special Ordered Sets type 1 (SOS1) This approach made it possible to solve the generated problems exactly for real-size problem instances.

The various facilities of a user-friendly and interactive man-machine interface (i.e. an input, planning, simulation and analysing module) turned out to be essential. Decision makers could easily change the data, and the generated plans, in a separate simulation module. However, the impact of any modification was immediately visualised by several (conflicting) indicators in the output screens, both on supply and demand level.

Study 4: Mixed Integer (0-1) Fractional Programming in Paper Production Industry

The study in Chapter 5 focussed on the impact of technical settings of production units on material flows. The main question was:” How to support decision-makers in practice if crucial properties of end products simultaneously depend on (endogenous) types of raw materials with different chemical or physical properties and (endogenous) technical settings of processing units?

The goal of the study was to revise and upgrade an existing, locally used DSS, to a tailored and flexible tool for decision support within the enterprise. The study revealed that the aimed extension towards multi-objective decision support, together with new physical insight for calculating properties of end products due to process operations, had a substantial impact on the optimization module.

The proposed solution procedure takes advantage of the problem characteristics and gives rise i) to apply and extend a classical reformulation approach for continuous linear fractional programming (FP) problems to a more general class of mixed integer (binary) FP problems and ii) to exploit the special structure between the original non- linear mixed integer model and the continuous, linear reformulation by applying the concept of Special Ordered Sets type 1 (SOS1).

Although Chapter 5 focusses in particular on the reformulation and solution approach, the DSS consists of four main building blocks, i.e. the user interface, a scenario manager, a simulation- and optimization routine. The optimization module provides a powerful tool to find feasible solutions and the best (unexpected) recipes for any available set of raw materials. Moreover, it provides an innovative way of decision support for purchasing (new) pulps on the market, for assigning available pulps to different paper grades, and for attuning available stock levels of raw materials to (changing) production targets for different paper grades. The results of the optimization routine are mainly used to obtain alternative recipes for different paper grades. Usually, these recipes are stored as base scenarios and adapted to daily practice in the simulation module.

Main conclusions and future research

Based on the studies in the Chapters 2 and 3 we conclude that no generically applicable models and/or solution approaches exist for simultaneous planning and scheduling in processing industries. More industry-specific solutions are needed incorporating specificities of different production environments into those models. The key to develop solvable approaches for contemporary practice may be i) to use knowledge and experience from practice and take advantage of specific characteristics in different problem domains during model construction, and/or ii) to identify and exploit special problem structures for solving the related models.

We conclude that surprisingly little research has been devoted to issues of coordination and integration between “procurement” and “production”. The studies in the chapters 4 and 5 confirm that sourcing of (raw) materials flows needs more attention in processing industries, particularly in push-oriented, inter-organizational networks. The valorisation of raw materials can be improved even more if the composition of raw materials is considered too in future planning problems at production level.

In the second part of this thesis we focused on extensions for the applicability of Special Ordered Sets type 1 (SOS1), both from an algorithmic (Chapter 4) and modelling (Chapter 5) point of view. We conclude that the concept of SOS1 can extend a classical reformulation approach for continuous fractional programming (FP) problems, to a specific class of mixed integer (0-1) FP problems. Moreover, we conclude that a natural ordering of the variables within the sets is not necessary to make their use worthwhile. A separate (user defined) reference row or weights associated to the variables in the sets might be omitted for an efficient use of SOS1 in commercially available mathematical programming packages. However, this requires further research and extensive computational tests.

De gezonde kas
Sikkema, A. ; Zijlstra, C. - \ 2014
Resource: weekblad voor Wageningen UR 9 (2014)6. - ISSN 1874-3625 - p. 16 - 17.
glastuinbouw - kastechniek - gewasbescherming - computer software - computertechnieken - beslissingsondersteunende systemen - gewasmonitoring - meetapparatuur - biologische bestrijding - landbouwkundig onderzoek - ziektepreventie - greenhouse horticulture - greenhouse technology - plant protection - computer techniques - decision support systems - crop monitoring - meters - biological control - agricultural research - disease prevention
Vier jaar onderzoek van Wageningen UR met dertig Duitse en Nederlandse partners in een Europees Interreg-project leverde 'De Gezonde Kas' op; een omvangrijk gewasbeschermingssysteem dat de tuinder vroegtijdig attendeert op ziekten en plagen, en hem adviseert over het nemen van gerichte maatregelen.
Akkerweb : Akkerweb uw perceel in beeld
Been, T.H. ; Molendijk, L.P.G. - \ 2014
akkerbouw - precisielandbouw - sensors - perceelsgrootte (landbouwkundig) - perceelsvorm (landbouwkundig) - beslissingsondersteunende systemen - gewasbescherming - plantenparasitaire nematoden - nematodenbestrijding - arable farming - precision agriculture - field size - field shape - decision support systems - plant protection - plant parasitic nematodes - nematode control
Akkerweb biedt de GIS-functionaliteit en enkele algemene generieke applicaties aan, zoals webservices om satelliet data te downloaden of de functionaliteit voor het genereren van een taakkaart.
Implementatie emissiemanagementsysteem grondgebonden teelten
Voogt, W. ; Balendonck, J. ; Heinen, M. ; Helm, F.P.M. van der; Janse, J. ; Swinkels, G.L.A.M. - \ 2014
Beiswijk : Wageningen UR Glastuinbouw (Rapport / Wageningen UR Glastuinbouw 1312)
glastuinbouw - cultuurmethoden - instrumenten (meters) - lysimeters - irrigatie - bemesting - emissie - optimalisatiemethoden - meting - beslissingsondersteunende systemen - greenhouse horticulture - cultural methods - instruments - irrigation - fertilizer application - emission - optimization methods - measurement - decision support systems
Bij telers bleek een sterke behoefte voor een eenvoudiger en goedkopere versie van de eerder ontwikkelde lysimeter met automatische drainmeter. Daarom is er een zogenaamde “light” versie van de lysimeter ontwikkeld, met een handmatige meting van de drain. Verder is er een inventarisatie gedaan naar alternatieven voor de eerder gebruikte vochtsensoren. Helaas zijn er (nog) geen sensoren die aan álle randvoorwaarden voldoen voor grondgebonden kasteelten. Met de ontwikkelde tools: lysimeter, drainmeter, sensoren en modellen, kan de watergift en bemesting geoptimaliseerd worden en bijdragen tot emissievermindering bij grondteelten. Bedrijven die de tools actief gebruiken bleken in staat de uitspoeling sterk te kunnen beperken. De interpretatie van vochtsensoren blijft een lastig fenomeen, vanwege de grote verschillen tussen grondsoorten en aspecten van de bedrijfsvoering. Dit vraagt de nodige ervaring die in de loop van meerdere teelten en jaren moet worden opgedaan. De resultaten van de waterbalansen op de bedrijven laten zien dat het goed mogelijk is de berekeningen via het verdampingsmodel en de gegevens van de lysimeter met elkaar in overeenstemming te brengen via een calibratiefactor.
Effective use of product quality information in food supply chain logistics
Rijpkema, W.A. - \ 2014
University. Promotor(en): Jack van der Vorst, co-promotor(en): Eligius Hendrix; Roberto Rossi. - Wageningen : Wageningen University - ISBN 9789461739490 - 183
logistiek - voedselvoorziening - ketenmanagement - voedselkwaliteit - beslissingsondersteunende systemen - modelleren - vlees - logistics - food supply - supply chain management - food quality - decision support systems - modeling - meat

Food supply chains have inherent characteristics, such as variability in product quality and quality decay, which put specific demands on logistics decision making. Furthermore, food supply chain organization and control has changed significantly in the past decades by factors such as scale intensification and globalization. In practice, these characteristics and developments frequently lead to supply chain problems, such as high levels of product waste, product quality problems, and high logistics costs. Recent technological developments have created the opportunity to gather, process, and communicate more information on the status of processes and products to support logistics decision making, providing business opportunities to realize performance improvements, and add extra value by differentiating products to specific market segments. This will, however, require the development of effective logistics management strategies that ensure the supply of products of appropriate quality in a cost-effective way to each stage of the supply chain. This thesis studies the use of product quality information in logistics decision making in food supply chains, captured in the following central research question:

How can the effectiveness of logistics decision making in food supply chains be improved using advanced product quality information?

This research question is investigated using four case studies: two in the context of the European Q-porkchains project (i.e. in pork supply chains), and two in the context of the European Veg-i-Trade project (i.e. in fruit- and vegetable supply chains). In these cases we investigated the impact of variability in product quality and quality decay on chain processes and studied if use of product quality information can improve logistics decision making regarding product sourcing and process design. In each case decision support models were developed – in close cooperation with industrial partners - to quantify the impact.

Case study 1: Process design for advanced sorting of meat products

The first case study, presented in chapter 2, considers the process design of a meat processing company that seeks to add value by sorting meat products for a specific product quality feature. The relation between product sorting, processing efficiency and process design is investigated using a discrete event simulation model. Results indicate that increasing sorting complexity by use of advanced product quality information results in a reduction of processing efficiency, whereas use of production buffers was found to mitigate negative effects of high sorting complexity.

The simulation allows practitioners facing segmented customer demand to assess which scenario offers the best trade-off between benefits and drawbacks resulting from efforts to improve responsiveness and flexibility.

Case study 2: Livestock sourcing decisions

The second case study considers a meat processing company that faces quality feature variation in animals delivered to its slaughterhouses. To support sourcing decisions and ensure that the right product quality is received at its slaughterhouses two stochastic programming models are developed that exploit product quality data gathered during earlier deliveries. The presented implementations reveal that uncertainty in supplied product quality can be reduced using historical farmer delivery data, which improves processing performance.

Case study 3: Product sourcing in international strawberry supply chains

The third case study relates to an international strawberry distributor that faces frequent product quality problems and substantial product waste. Different sourcing strategies were tested using a combination of both a slow, but cheap transport mode (i.e. sea and truck), and a faster, but more expensive mode (i.e. plane). The performance of these sourcing strategies is examined using a discrete-continuous chain simulation that includes microbiological growth models to predict quality decay. Simulation results reveal that standard cost parameters (that do not take quality decay into account) result in substantial product waste, but if cost for expected shelf-life losses are included in the order policies the effectiveness of product sourcing for the considered supply chain is improved.

Case study 4: Use of form postponement for food waste reduction

The fourth case study concerns an international lettuce supply chain that struggles with effective product sourcing. Form postponement (FP) is a supply chain strategy which delays processing steps until a demand is realized. This allows a reduction of the total inventory in the supply chain. We studied supply chain scenarios that differ in where and when in the supply chain whole crop lettuce is converted into processed lettuce products. A discrete-continuous chain simulation model revealed that application of FP reduced both product waste and age and improves point-of-sale product quality.

Integrated findings

The findings of this thesis demonstrate that decision makers can improve logistics decisions and reduce food waste by using product quality information and predicting changes in product quality. The developed quantitative decision support models provided essential insights into trade-offs resulting from information-based supply chain performance improvement strategies. The presented case studies demonstrate that supply chain flexibility and responsiveness is required to reduce the impact of product variability and product quality decay. Increasing responsiveness and flexibility typically comes at the expense of other performance dimensions.

This research demonstrates the potential of use of product quality information in food supply chain logistics, which may contribute to the effectiveness of food supply chains by improving consumer satisfaction, reducing overall costs, and reducing food waste.

Decision support modeling for milk valorization
Banaszewska, A. - \ 2014
University. Promotor(en): Jack van der Vorst, co-promotor(en): Frans Cruijssen. - Wageningen : Wageningen University - ISBN 9789461739261 - 182
operationeel onderzoek - modelleren - melk - beslissingsondersteunende systemen - beslissingsmodellen - rentabiliteit - zuivelindustrie - rauwe melk - melkbewerking - nederland - efficiëntie - operations research - modeling - milk - decision support systems - decision models - profitability - dairy industry - raw milk - milk processing - netherlands - efficiency

The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to optimally utilize raw milk (the main raw material) in all business units. The main goal of this research was the development and application of decision support models to help MVA attain its mission of “getting more out of milk.”

The dairy processing industry is a specific and challenging research field. This is related to the fact that the raw milk is transformed into thousands of end products via highly interrelated production processes. These processes are affected by uncertainties related to supply, processing capacities, and demand. Attaining high profitability requires a central, integral planning process that facilitates the optimal allocation of raw milk to a large range of products. Optimal allocation of raw milk is achieved when it is successfully allocated to the most profitable end products and all important constraints are taken into account. This process is defined as milk valorization. Contribution to the improvement of milk valorization in the dairy industry was the main objective of this thesis. We approached the problem from a Logistics Management perspective. We focused on decisions supporting the optimal flow of raw materials to end products, from farmers to consumer markets. With the use of Operations Research techniques, we developed quantitative models and frameworks to improve the mid-term milk valorization process.

As the first step towards the improvement of milk valorization we developed a mid-term Dairy Valorization Model (DVM). The model creates optimal plans for the allocation of milk, and the production of end products and byproducts. It captures the dynamics of dairy production and incorporates all relevant elements and constraints. The following elements were indicated as important and included in the DVM: recipes based on raw milk composition (dry matter, fat, and protein content); seasonality of raw milk composition and supply; a complete dairy product portfolio; by-product utilization; network of supply regions and production locations; by-product and raw milk transportation; and changes in sale prices. Including all relevant elements assures DVM comprehensiveness. This important aspect achieves truly integral valorization of milk. Furthermore, the developed DVM also fosters understanding of complex, underlying production processes. Moreover, by means of additional analysis we have also shown that the seasonality of raw milk components (dry matter, fat and protein) plays an important role in the valorization process. It considerably affects decisions regarding milk allocation to end products (up to 50% difference in production volumes of clustered end products) and company profit (up to 4% difference in monthly profit).

Given the complexity of the dairy system, the development of a high class valorization model required a gradual approach. The developed DVM focuses on the valorization of milk-based end products (main milk products). The production of those products, however, results in large volumes of byproducts.In the second step of this research we investigated the effect of whey valorization (byproduct of cheese) on the valorization of main milk products, as well as the added value of integral valorization (simultaneous valorization of both main and byproducts). We developed a new Integral Dairy Valorization model (IDVM) to allow for an integral milk valorization. We also developed a three-step evaluation approach to compare results of stepwise valorization (in which whey valorization only follows after main milk products valorization) and integral valorization. The results show that the explicit valorization of whey flows leads to significant economic gains for FC. Profit obtained from post processing of whey byproducts amounts to circa 20% of the total profit. Furthermore, the effect of integrating both valorization processes is currently small (on average 0.0089% increase in monthly profit). There is, however, a potential in the integration of two processes. In case demand for, and sale prices of, whey-based products, sale prices of milk powders or processing capacity for whey increases, the gain from the integration can be considerably larger (up to 1200% stronger effect in comparison to the current situation). We have also shown that currently whey products are not profitable enough to drive the production of milk products that are the source of the whey by-product.

In the next step we focused on the accuracy of solutions obtained with the DVM. Because the DVM is a deterministic model, uncertainties present in input are not incorporated, and as such the stability of valorization plans is affected. Stability of plans is often referred as to the ‘robustness’ of plans: the degree to which the optimal solution might change if realization of certain input parameters turn out to be different than the forecasted values. The robustness is important, because the valorization plans that are initially indicated as optimal can easily become sub-optimal or costly. Therefore, the overall goal of the third study was to develop a framework for robustness evaluation of valorization plans obtained with deterministic models. We developed a five-step framework comprised of the following: (1) definition of Key Performance Indicators (KPIs), (2) selection of relevant input parameters, (3) definition of scenarios, (4) evaluation of robustness, and (5) extraction of conclusions. The output from Step 4 of the framework is multidimensional, and thus to arrive at the final robustness degree, a number of decisions must be made a priori: acceptable KPIs limits (robustness bounds); evaluation time (month or year); evaluation depth (parameter or element); and the grouping approach of KPIs. The results show that depending on the selection of these aspects different conclusions regarding robustness of valorization plans are obtained, (average robustness degree varied from 48% to 92%), and thus the final conclusions regarding the robustness degree of plans is affected. The overall robustness degree of valorization plans (at FC) obtained with the DVM was 90% and was indicated by FC as sufficiently high to attain successful milk valorization. The calculated robustness degrees also identified the parameters with the greatest effect on robustness (composition and supply of milk).

The effectiveness of valorization models is mainly linked to the optimality, feasibility and robustness of obtained plans. However, even if these three aspects are satisfied, the success of the valorization process is still very much dependent on the performance level of actors and units that are involved in the process. Given the fact that processing units (factories) are the most important units in the supply chain of a processing company, because they can easily affect the value of each ton of raw milk used in the production process, the last study investigated the performance of processing units. We developed two Data Envelopment Analysis models for performance measurement and improvement, and applied it to the case study of TNT Express. The models allowed us to identify: inefficient units (30%); parts of efficiency levels (of inefficient units) that result from either management practices (85%) or a favorable external environment (15%); potential reductions in consumed input resources that allow for the same output levels (17% less labor and subcontractors could be used); and role models that can be treated as master units in efficient use of certain inputs and thus should play leading roles in setting benchmarks.

We concluded that in order to successfully valorize raw materials, companies should: develop their own valorization model, possess a comprehensible overview of the complete production system; and have access to necessary input data. Furthermore, there is a potential in integrating main product and by-product valorization processes. The added value, however, depends on the information on market and production capacities of by-products and related to them main products. To ensure that possible future integration of both valorizations processes occurs correctly, companies should investigate future market developments and the possibility of increasing production capacity. Moreover, we have also shown that robustness of solutions obtained with deterministic valorization models can be sufficiently high to obtain reliable plans. This means that it is not always necessary to implement complex modeling techniques (such as stochastic programming). To ensure accurate solutions, companies should also focus on improving forecast accuracies of parameters affecting the robustness. The robustness degree should also be regularly assessed with the developed framework. Finally, managers should also focus on performance levels of processing units. A DEA model should be developed to identify inefficient factories and provide new insights to improve performance.

In order to properly valorize milk or other food resources to its maximum an integral point of view should be chosen. Operations Research techniques should be used because the complexity of many processing industries makes applying practical rules of thumb insufficient and often inadequate. The models and frameworks developed in this thesis provide new perspective on and new insights into the complex problem of milk valorizations. We have shown that analyses of results obtained with the developed methods can answer many managerial questions, and thus support the decision making process within a company. This improves overall raw material valorization, creates more value for companies, and leads to more sustainable dairy chains.

Onderzoek Sclerotinia in 2012 - Sclerotiën, sporen, BOS en spuittechniek
Wanders, J. ; Russchen, H.J. ; Lamers, J.G. - \ 2014
Kennisakker.nl
sclerotinia sclerotiorum - bodempathogenen - plantenziekteverwekkende schimmels - plantenziektebestrijding - sclerotia - spuiten - beslissingsondersteunende systemen - akkerbouw - vollegrondsgroenten - gewasbescherming - soilborne pathogens - plant pathogenic fungi - plant disease control - spraying - decision support systems - arable farming - field vegetables - plant protection
Sclerotinia sclerotiorum is een bodemgebonden schimmelziekte. In Nederland neemt de problematiek met Sclerotinia in akkerbouw- en tuinbouwgewassen steeds meer toe. Zo ook in de aardappelteelt en dan vooral op zandgronden.
Onderzoek Sclerotinia in 2012 : Sclerotiën, sporen, BOS en spuittechniek
Wanders, J. ; Russchen, H.J. ; Lamers, J.G. ; Lange, J. de; Akker, H. van den; Roessel, G.J. van - \ 2014
Dronten : DLV Plant - 53
sclerotinia - sclerotinia sclerotiorum - schimmelziekten - beslissingsondersteunende systemen - gewasbescherming - vollegrondsgroenten - vollegrondsteelt - veldproeven - ascosporen - akkerbouw - spuiten - bonen - penen - cichorium intybus - aardappelen - fungal diseases - decision support systems - plant protection - field vegetables - outdoor cropping - field tests - ascospores - arable farming - spraying - beans - carrots - potatoes
De problemen met Sclerotinia (rattenkeutelziekte), veroorzaakt door de schimmel Sclerotinia sclerotiorum, nemen de laatste jaren steeds meer toe. In diverse vollegrondsgroenten is Sclerotinia een van de belangrijkste ziekten. Om te komen tot een integrale aanpak van de problematiek is er door de Productschappen Tuinbouw en Akkerbouw voor 2012 gekozen voor een gezamenlijke financiering van een aantal onderzoeksthema's die ondergebracht zijn bij de onderzoeksinstellingen DLV Plant, PPO-AGV en Proeftuin Zwaagdijk. Deze thema’s waren: speuren naar sporen; aantal sclerotiën; beslissingsondersteunende systemen (BOS); spuittechniek.
Interpoleren kun je leren : een beslissingsondersteunend systeem voor interpolatie, aggregatie en desaggregatie in ruimte en tijd
Walvoort, D.J.J. ; Knotters, M. - \ 2013
Wageningen : Wettelijke Onderzoekstaken Natuur & Milieu (WOt-paper 26)
bodemchemie - kriging - zink - beslissingsondersteunende systemen - methodologie - kaarten - soil chemistry - zinc - decision support systems - methodology - maps
Tijd en geld ontbreken meestal om overal en altijd waarnemingen te verrichten. Daarom moeten in vrijwel elk onderzoek gegevens worden geïnterpoleerd naar niet-bezochte locaties of tijdstippen. Ook moeten gegevens vaak worden geaggregeerd tot bijvoorbeeld ruimtelijke of temporele totalen of gemiddelden, of worden gedesaggregeerd van grote naar kleine ruimtelijke of temporele eenheden. Dat kan op vele manieren, maar welke manier is het meest geschikt? Om onderzoekers te helpen bij het maken van een gefundeerde keuze hebben we een website met een beslissingsondersteunend systeem ontworpen, die we in deze paper onder de aandacht brengen (www.mapmakersguide.org). Voorbeelden maken duidelijk dat de keuze van de juiste interpolatie-, aggregatieof desaggregatiemethode er wel degelijk toe doet.
Map maker’s guide: a decision support system for interpolation, aggregation, and disaggregation : technical documentation
Walvoort, D.J.J. ; Knotters, M. ; Hoogland, T. ; Wijnen, H. van; Dijk, T.A. van; Schöll, L. van; Groenenberg, J.E. - \ 2013
Wageningen : Wettelijke Onderzoekstaken Natuur & Milieu (WOt-werkdocument 350) - 36
kaarten - beslissingsondersteunende systemen - tijd - ruimte - aggregatie - internet - maps - decision support systems - time - space - aggregation
This report documents a decision support system (DSS) that has been developed to assist environmental researchers in selecting interpolation, aggregation, and disaggregation methods. The DSS has been implemented as a web-application. This facilitates updating and makes the DSS generally accessible. The DSS asks the user several questions. The answers are compared with those given by experts. The degree of similarity between both sets of answers is used to assign suitability scores to a huge set of interpolation, aggregation, and disaggregation methods stored in a database. These methods are ranked from most to least suitable and presented to the user in a dynamic table. The user can compare recommended methods (backgrounds, available software, literature, performance) and evaluate dynamically which methods would have been recommended if deferent answers had been given (what-if analysis)
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