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Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

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  • Muppani (Muppant), Venkata Reddy
  • Adil, Gajendra Kumar

Abstract

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.

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  • Muppani (Muppant), Venkata Reddy & Adil, Gajendra Kumar, 2008. "Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach," Omega, Elsevier, vol. 36(4), pages 609-618, August.
    • Handle: RePEc:eee:jomega:v:36:y:2008:i:4:p:609-618
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    7. Ene, Seval & Küçükoğlu, İlker & Aksoy, Aslı & Öztürk, Nursel, 2016. "A genetic algorithm for minimizing energy consumption in warehouses," Energy, Elsevier, vol. 114(C), pages 973-980.
    8. Bo Yan & Chang Yan & Feng Long & Xing-Chao Tan, 2018. "Multi-objective optimization of electronic product goods location assignment in stereoscopic warehouse based on adaptive genetic algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1273-1285, August.
    9. Syam, Siddhartha S. & Côté, Murray J., 2010. "A location-allocation model for service providers with application to not-for-profit health care organizations," Omega, Elsevier, vol. 38(3-4), pages 157-166, June.
    10. Zhang, Guoqing & Shang, Xiaoting & Alawneh, Fawzat & Yang, Yiqin & Nishi, Tatsushi, 2021. "Integrated production planning and warehouse storage assignment problem: An IoT assisted case," International Journal of Production Economics, Elsevier, vol. 234(C).
    11. Wang, Ning & Jin, Bo & Lim, Andrew, 2015. "Target-guided algorithms for the container pre-marshalling problem," Omega, Elsevier, vol. 53(C), pages 67-77.
    12. Correia, Isabel & Melo, Teresa & Saldanha-da-Gama, Francisco, 2012. "Comparing classical performance measures for a multi-period, two-echelon supply chain network design problem with sizing decisions," Technical Reports on Logistics of the Saarland Business School 1, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    13. Zhang, Guoqing & Nishi, Tatsushi & Turner, Sarina D.O. & Oga, Keisuke & Li, Xindan, 2017. "An integrated strategy for a production planning and warehouse layout problem: Modeling and solution approaches," Omega, Elsevier, vol. 68(C), pages 85-94.
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