Robust possibilistic programming for joint order batching and picker routing problem in warehouse management

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Yousefi Nejad Attari, Mahdi and Ebadi Torkayesh, Ali and Malmir, Behnam and Neyshabouri Jami, Ensiyeh (2021) Robust possibilistic programming for joint order batching and picker routing problem in warehouse management. International Journal of Production Research, 59 (14). pp. 4434-4452. ISSN 0020-7543 (Print) 1366-588X (Online)

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Abstract

Decisions made for designing and operating a warehouse system are of great significance. These operational decisions are strongly affected by total logistics costs, including investment and direct operating costs. The number of orders made by customers in the logistics section of warehouse management is very high because the number, type of products and items ordered by different customers vary broadly. However, machines layout for picking up products at logistics centres is minimal, inflexible, and, in some cases, inconclusive. In this study, we address joint order batching procedures of orders considering picker routing problem as a mixed-integer programming model. Extensive numerical experiments were generated in small, medium, and large sizes. In order to consider the uncertainty of parameters, we applied robust possibilistic programming for this problem. Three different meta-heuristic algorithms; genetic algorithm, particle swarm optimisation algorithm, and honey artificial bee colony algorithms are used as solution approaches to solve the formulated model. The performance of solution approaches over the problem was analysed using several test indexes. In all three group examples, there was no significant difference among mean values of the objective function, while there was a remarkable difference among computing times.
Item Type: Article
Uncontrolled Keywords: artificial bee colony algorithms; genetic algorithm; joint order batching; particle swarm optimisation algorithm; picker routing; warehouse design; warehousing systems
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Ali Ebadi Torkayesh
Date Deposited: 02 Sep 2022 16:12
Last Modified: 02 Sep 2022 16:12
URI: https://research.sabanciuniv.edu/id/eprint/43372

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