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 408354
Title A State Space Augmentation Algorithm for the Replenishment Cycle Inventory Policy
Author(s) Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.D.
Source International Journal of Production Economics 133 (2011)1. - ISSN 0925-5273 - p. 377 - 384.
Department(s) Operations Research and Logistics
Information Technology
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) service-level constraints - shortest-path problem - lot-sizing problem - strategies
Abstract In this work we propose an efficient dynamic programming approach for computing replenishment cycle policy parameters under non-stationary stochastic demand and service level constraints. The replenishment cycle policy is a popular inventory control policy typically employed for dampening planning instability. The approach proposed in this work achieves a significant computational efficiency and it can solve any relevant size instance in trivial time. Our method exploits the well known concept of state space relaxation. A filtering procedure and an augmenting procedure for the state space graph are proposed. Starting from a relaxed state space graph our method tries to remove provably suboptimal arcs and states (filtering) and then it tries to efficiently build up (augmenting) a reduced state space graph representing the original problem. Our experimental results show that the filtering procedure and the augmenting procedure often generate a small filtered state space graph, which can be easily processed using dynamic programming in order to produce a solution for the original problem.
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