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Genetic Algorithm for Scattered Storage Assignment in Kiva Mobile Fulfillment System
School of Information, Beijing Wuzi University, Beijing, China
School of Information, Beijing Wuzi University, Beijing, China
- 1 School of Information, Beijing Wuzi University, Beijing, China
- 2 School of Information, Beijing Wuzi University, Beijing, China
American Journal of Operations Research·Volume 08 (2018)·Pages 474–485·Published 29 October 2018·DOI10.4236/ajor.2018.86027
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Abstract
Scattered storage means an item can be stored in multiple inventory bins. The scattered storage assignment problem based on association rules in Kiva mobile fulfillment system is investigated, which aims to decide the pods for each item to put on so as to minimize the number of pods to be moved when picking a batch of orders. This problem is formulated into an integer programming model. A genetic algorithm is developed to solve the large-sized problems. Computational experiments and comparison between the scattered storage strategy and random storage strategy are conducted to evaluate the performance of the model and algorithm.
KeywordsScattered Storage AssignmentKiva Mobile Fulfillment SystemAssociation RulesGenetic Algorithm
- Wurman, P.R., D’Andrea, R. and Mountz, M. (2008) Coordinating Hundreds of Cooperative, Autonomous Vehicles in Warehouses. Ai Magazine, 29, 9-20.
- Enright, J. and Wurman, P.R. (2011) Optimization and Coordinated Autonomy in Mobile Fulfillment Systems. Autom. Action Plan. Automated Action Planning for Autonomous Mobile Robots from 2011 AAAI Workshop, San Francisco, California, USA, 7 August 2011, 1-1.
- Roodbergen, K.J. and De Koster, R. (2001) Routing Order Pickers in a Warehouse with a Middle Aisle. European Journal of Operational Research, 133, 32-43. https://doi.org/10.1016/S0377-2217(00)00177-6
- Accorsi, R., Baruffaldi, G. and Manzini, R. (2018) Picking Efficiency and Stock Safety: A Bi-Objective Storage Assignment Policy for Temperature-Sensitive Products. Computers & Industrial Engineering, 115, 240-252. https://doi.org/10.1016/j.cie.2017.11.009
- Quader, S. and Castillo-Villar, K.K. (2018) Design of an Enhanced Multi-Aisle Order-Picking System Considering Storage Assignments and Routing Heuristics. Robotics and Computer-Integrated Manufacturing, 50, 13-29. https://doi.org/10.1016/j.rcim.2015.12.009
- Davis, C.J. (2017) Using Self-Organizing Maps to Cluster Products for Storage Assignment in a Distribution Center.
- Chang, Y., Ma, W. and Wu, Y. (2017) Principles of Storage Location Assignment in Multi-Tier Shuttle Warehouse System. Chinese Automation Congress (CAC), Jinan, 20-22 October 2017, 5658-5662. https://doi.org/10.1109/CAC.2017.8243792
- de Koster, R., Le-Duc, T. and Roodbergen, K.J. (2007) Design and Control of Warehouse Order Picking: A Literature Review. European Journal of Operational Research, 182, 481-501. https://doi.org/10.1016/j.ejor.2006.07.009
- Il-Choe, K. and Sharp, G. (2014) Small Parts Order Picking: Design and Operation.
- Hausman, W.H., Schwarz, L.B. and Graves, S.C. (1976) Optimal Storage Assignment in Automatic Warehousing Systems. Management Science, 22, 629-638. https://doi.org/10.1287/mnsc.22.6.629
- De Koster, M.B.M. and Neuteboom, A.J. (2001) The Logistics of Supermarket Chains. Elsevier, Doetinchem, The Netherlands.
- Heskett, J.L. (1963) Cube-Per-Order Index: A Key to Warehouse Stock Location. Transportation and Distribution Management, 3, 27-31.
- Malmborg, C.J. and Bhaskaran, K. (1990) A Revised Proof of Optimality for the Cube-Per-Order Index Rule for Stored Item Location. Applied Mathematical Modelling, 14, 87-95. https://doi.org/10.1016/0307-904X(90)90076-H