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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Record number 494015
Title Using multi-objective calibration techniques to assess impacts of climate change at farm level
Author(s) Kanellopoulos, A.; Reidsma, P.; Bloemhof-Ruwaard, J.M.; Claassen, G.D.K.
Event 27th European Conference on Operational Research, Glasgow, UK, 2015-07-12/2015-07-15
Department(s) Operations Research and Logistics
Plant Production Systems
Publication type Abstract in scientific journal or proceedings
Publication year 2015
Abstract Assessing the impact of climate change on agricultural systems requires whole farm optimization models that can be used to simulate the behaviour of farmers and evaluate future adaptation strategies within scenarios of climate change. A good representation of the multi-objective nature of farmer’s decision making is essential for accurate model predictions. Often in existing studies for reasons of simplification the multi-objective nature of the farmer’s decision making is ignored and the existence of a single economic objective that drives the decision making process is assumed. In these studies, calibration techniques like Positive Mathematical Programming are used to recover unknown parameters of a non-linear cost function based on historical decisions. However, the existence of multiple objectives in farmers decision making is ignored which might affect the predictive capacity of whole farm optimization models. We use a novel multi-objective calibration technique to recover the unknown parameters of a non-linear Compromise Programming model. The proposed calibration method accounts for multiple conflicting objectives, improves the predictive capacity of the model and relaxes assumptions underlying the calibration process. We apply the calibrated model to evaluate the impact of climate change scenarios and future adaptation strategies of arable farmers in the Netherlands.
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