An efficient data-driven method for storage location assignment under item correlation considerations

References

• Accorsi, Riccardo, Manzini, Riccardo, & Bortolini, Marco. (2012). A hierarchical procedure for storage allocation and assignment within an order-picking system. A case study. International Journal of Logistics Research and Applications, 15(6), 351–364. http://dx.doi.org/10.1080/13675567.2012.742877
   Web of Science ®Google Scholar
• Alyahya, S., Wang, Q., & Bennett, N. (2016). Application and integration of an RFID-enabled warehousing management system – a feasibility study. Journal of Industrial Information Integration, 4, 15–25. https://doi.org/10.1016/j.jii.2016.08.001
   Web of Science ®Google Scholar
• Atashgar, K., & Zargarabadi, O. (2017). Monitoring multivariate profile data in plastic parts manufacturing industries: An intelligently data processing. Journal of Industrial Information Integration, 8, 38–48. https://doi.org/10.1016/j.jii.2017.06.003
   Web of Science ®Google Scholar
• Atmaca, E., & Ozturk, A. (2013). Defining order picking policy: A storage assignment model and a simulated annealing solution in AS/RS systems. Applied Mathematical Modelling, 37(7), 5069–5079. https://doi.org/10.1016/j.apm.2012.09.057
   Web of Science ®Google Scholar
• Aziz, A. A., Mousavi, S. M., Tavana, M., & Niaki, S. T. A. (2020). An investigation of the robustness in the Travelling Salesman problem routes using special structured matrices. International Journal of Systems Science: Operations & Logistics, 7(2), 172–181. https://doi.org/10.1080/23302674.2018.1551584
   Web of Science ®Google Scholar
• Barletta, C., Garn, W., Turner, C., & Fallah, S. (2022). Hybrid fleet capacitated vehicle routing problem with flexible Monte–Carlo tree search. International Journal of Systems Science: Operations & Logistics, 1–17. https://doi.org/10.1080/23302674.2022.2102265
   Google Scholar
• Battini, D., Calzavara, M., Persona, A., & Sgarbossa, F. (2015). Order picking system design: The storage assignment and travel distance estimation (SA&TDE) joint method. International Journal of Production Research, 53(4), 1077–1093. https://doi.org/10.1080/00207543.2014.944282
   Web of Science ®Google Scholar
• Battista, C, Fumi, A, Laura, L, Schiraldi, M. (2014). Multiproduct slot allocation heuristic to minimize storage space. International Journal of Retail and Distribution Management, 42(3), 172–186.
   Google Scholar
• Bindi, Filippo, Manzini, Riccardo, Pareschi, Arrigo, & Regattieri, Alberto. (2009). Similarity-based storage allocation rules in an order picking system: an application to the food service industry. International Journal of Logistics Research and Applications, 12(4), 233–247. http://dx.doi.org/10.1080/13675560903075943
   Web of Science ®Google Scholar
• Bodnar, Peter, & Lysgaard, Jens. (2017). A dynamic programming algorithm for the space allocation and aisle positioning problem. Journal of the Operational Research Society, 65(9), 1315–1324. http://dx.doi.org/10.1057/jors.2013.64
   Google Scholar
• Boysen, N., De Koster, R., & Weidinger, F. (2019). Warehousing in the e-commerce era: A survey. European Journal of Operational Research, 277(2), 396–411. https://doi.org/10.1016/j.ejor.2018.08.023
   Web of Science ®Google Scholar
• Carlo, Héctor J, & Giraldo, Germán E.. (2012). Toward perpetually organized unit-load warehouses. Computers & Industrial Engineering, 63(4), 1003–1012. http://dx.doi.org/10.1016/j.cie.2012.06.012
   Web of Science ®Google Scholar
• Caron, F., Marchet, G., & Perego, A. (2000). Layout design in manual picking systems: A simulation approach. Integrated Manufacturing Systems, 11(2), 94–104. https://doi.org/10.1108/09576060010313946
   Google Scholar
• Cavalcante, C. A. V. (2019). Order planning policies for business-to-consumer e-tail stores. Computers & Industrial Engineering, 136, 106–116. https://doi.org/10.1016/j.cie.2019.07.010
   Web of Science ®Google Scholar
• Çelk, Melh, & Süral, Haldun. (2014). Order picking under random and turnover-based storage policies in fishbone aisle warehouses. IIE Transactions, 46(3), 283–300. http://dx.doi.org/10.1080/0740817X.2013.768871
   Web of Science ®Google Scholar
• Chen, Lu, Langevin, André, & Riopel, Diane. (2010). The storage location assignment and interleaving problem in an automated storage/retrieval system with shared storage. International Journal of Production Research, 48(4), 991–1011. http://dx.doi.org/10.1080/00207540802506218
   Web of Science ®Google Scholar
• Chen, Lu, Langevin, André, & Riopel, Diane. (2011). A tabu search algorithm for the relocation problem in a warehousing system. International Journal of Production Economics, 129(1), 147–156. http://dx.doi.org/10.1016/j.ijpe.2010.09.012
   Web of Science ®Google Scholar
• Chen, Lu, Riopel, Diane, & Langevin, Andre. (2009). Minimising the peak load in a shared storage system based on the duration-of-stay of unit loads. International Journal of Shipping and Transport Logistics, 1(1), 20. http://dx.doi.org/10.1504/IJSTL.2009.021974
   Web of Science ®Google Scholar
• Cheng, Y., Chen, K., Sun, H., Zhang, Y., & Tao, F. (2018). Data and knowledge mining with big data towards smart production. Journal of Industrial Information Integration, 9, 1–13. https://doi.org/10.1016/j.jii.2017.08.001
   Web of Science ®Google Scholar
• Chiang, D. M. H., Lin, C. P., & Chen, M. C. (2011). The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres. Enterprise Information Systems, 5(2), 219–234. https://doi.org/10.1080/17517575.2010.537784
   Web of Science ®Google Scholar
• Chiang, D. M. H., Lin, C. P., & Chen, M. C. (2014). Data mining based storage assignment heuristics for travel distance reduction. Expert Systems, 31(1), 81–90. https://doi.org/10.1111/exsy.12006
   Web of Science ®Google Scholar
• Chou, Yon-Chun, Chen, Yao-Hung, & Chen, Hui-Min. (2012). Recency-based storage assignment and warehouse configuration for recurrent demands. Computers & Industrial Engineering, 62(4), 880–889. http://dx.doi.org/10.1016/j.cie.2011.12.009
   Web of Science ®Google Scholar
• Chuang, Y.-F., Lee, H.-T., & Lai, Y.-C. (2012). Item-associated cluster assignment model on storage allocation problems. Computers & Industrial Engineering, 63(4), 1171–1177. https://doi.org/10.1016/j.cie.2012.06.021
   Web of Science ®Google Scholar
• Cinar, D., Oliveira, J. A., Topcu, Y. I., & Pardalos, P. M. (2017). Scheduling the truckload operations in automated warehouses with alternative aisles for pallets. Applied Soft Computing, 52, 566–574. https://doi.org/10.1016/j.asoc.2016.10.013
   Web of Science ®Google Scholar
• Dijkstra, Arjan S, & Roodbergen, Kees Jan. (2017). Exact route-length formulas and a storage location assignment heuristic for picker-to-parts warehouses. Transportation Research Part E: Logistics and Transportation Review, 102, 38–59. http://dx.doi.org/10.1016/j.tre.2017.04.003
   Web of Science ®Google Scholar
• Elbert, R., & Müller, J. P. (2017). The impact of item weight on travel times in picker-toparts order picking: An agent-based simulation approach. In 2017 Winter Simulation Conference (WSC) (pp. 3162-3173). IEEE.
   Google Scholar
• Ene, S, Küçükoğlu, İ., Aksoy, A., & Öztürk, N. (2016). A genetic algorithm for minimizing energy consumption in warehouses. Energy, 114, 973–980. https://doi.org/10.1016/j.energy.2016.08.04
   Web of Science ®Google Scholar
• Ene, S., & Öztürk, N. (2012). Storage location assignment and order picking optimization in the automotive industry. The international journal of advanced manufacturing technology, 60, 787–797.
   Google Scholar
• Fontana, M. E., & Cavalcante, C. A. V. (2014). Use of Promethee method to determine the best alternative for warehouse storage location assignment. The International Journal of Advanced Manufacturing Technology, 70, 1615–1624.
   Web of Science ®Google Scholar
• Franzke, T., Grosse, E. H., Glock, C. H., & Elbert, R. (2017). An investigation of the effects of storage assignment and picker routing on the occurrence of picker blocking in manual picker-to-parts warehouses. The International Journal of Logistics Management.
   Google Scholar
• Frazelle, E. H.. (1989). Stock location assignment and order picking productivity PhD thesis, Georgia Institute of Technology, Atlanta.
   Google Scholar
• Fukunari, M, & Malmborg, C. J. (2008). A heuristic travel time model for random storage systems using closest open location load dispatching. International Journal of Production Research, 46(8), 2215–2228. http://dx.doi.org/10.1080/00207540601118462
   Web of Science ®Google Scholar
• Fumi, Andrea, Scarabotti, Laura, & Schiraldi, Massimiliano M. (2013). Minimizing Warehouse Space with a Dedicated Storage Policy. International Journal of Engineering Business Management, 5, 21. http://dx.doi.org/10.5772/56756
   Google Scholar
• Gagliardi, Jean-Philippe, Renaud, Jacques, & Ruiz, Angel. (2012). On storage assignment policies for unit-load automated storage and retrieval systems. International Journal of Production Research, 50(3), 879–892. http://dx.doi.org/10.1080/00207543.2010.543939
   Web of Science ®Google Scholar
• Gagliardi, Jean-Philippe, Renaud, Jacques, & Ruiz, Angel. (2014). On sequencing policies for unit-load automated storage and retrieval systems. International Journal of Production Research, 52(4), 1090–1099. http://dx.doi.org/10.1080/00207543.2013.838331
   Web of Science ®Google Scholar
• Gagliardi, J. P., Renaud, J., & Ruiz, A. (2014). A simulation modeling framework for multiple-aisle automated storage and retrieval systems. Journal of Intelligent Manufacturing, 25, 193–207.
   Web of Science ®Google Scholar
• Garfinkel, M. (2015). Minimizing multi-zone orders in the correlated storage assignment problem. PhD thesis, Georgia Institute of Technology, Atlanta.
   Google Scholar
• Glock, Christoph H, & Grosse, Eric H.. (2012). Storage policies and order picking strategies in U-shaped order-picking systems with a movable base. International Journal of Production Research, 50(16), 4344–4357. http://dx.doi.org/10.1080/00207543.2011.588621
   Web of Science ®Google Scholar
• Grosse, E. H., Glock, C. H., & Neumann, W. P. (2017). Human factors in order picking: A content analysis of the literature. International Journal of Production Research, 55(5), 1260–1276. https://doi.org/10.1080/00207543.2016.1186296
   Web of Science ®Google Scholar
• Grosse, Eric H., Glock, Christoph H., & Jaber, Mohamad Y. (2013). The effect of worker learning and forgetting on storage reassignment decisions in order picking systems. Computers & Industrial Engineering, 66(4), 653–662. http://dx.doi.org/10.1016/j.cie.2013.09.013
   Web of Science ®Google Scholar
• Gu, Jinxiang, Goetschalckx, Marc, & McGinnis, Leon F. (2007). Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177(1), 1–21. http://dx.doi.org/10.1016/j.ejor.2006.02.025
   Web of Science ®Google Scholar
• Gue, K. R., Meller, R. D., & Skufca, J. D. (2006). The effects of pick density on order picking areas with narrow aisles. IIE Transactions, 38(10), 859–868. https://doi.org/10.1080/07408170600809341
   Web of Science ®Google Scholar
• Guerriero, F., Musmanno, R., Pisacane, O., & Rende, F.. (2013). A mathematical model for the Multi-Levels Product Allocation Problem in a warehouse with compatibility constraints. Applied Mathematical Modelling, 37(6), 4385–4398. http://dx.doi.org/10.1016/j.apm.2012.09.015
   Web of Science ®Google Scholar
• Guerriero, F., Pisacane, O., & Rende, F. (2015). Comparing heuristics for the product allocation problem in multi-level warehouses under compatibility constraints. Applied Mathematical Modelling, 39(23-24), 7375–7389. https://doi.org/10.1016/j.apm.2015.02.047
   Web of Science ®Google Scholar
• Hahn, H. (1932). Ergebnisse eines mathematischen Kolloquiums. Monatshefte für Mathematik und Physik, 39(1), A8–A8. https://doi.org/10.1007/BF01699094
   Google Scholar
• Han, J., & Kamber, M. (2000). Data mining: Concepts and techniques, 13-16.
   Google Scholar
• Haq, A. A. U., & Djurdjanovic, D. (2019). Dynamics-inspired feature extraction in semiconductor manufacturing processes. Journal of Industrial Information Integration, 13, 22–31. https://doi.org/10.1016/j.jii.2018.12.001
   Web of Science ®Google Scholar
• Jane, Chin-Chia, & Laih, Yih-Wenn. (2005). A clustering algorithm for item assignment in a synchronized zone order picking system. European Journal of Operational Research, 166(2), 489–496. http://dx.doi.org/10.1016/j.ejor.2004.01.042
   Web of Science ®Google Scholar
• Koetsier, J. (2023). E-Commerce retail just passed $1 trillion for the first time ever. Forbes. https://www.forbes.com/sites/johnkoetsier/2023/01/28/
   Google Scholar
• Kofler, M., Beham, A., Wagner, S., Affenzeller, M., & Achleitner, W. (2011, August). Re-warehousing vs. healing: Strategies for warehouse storage location assignment. In 3rd IEEE international symposium on logistics and industrial informatics (pp. 77–82). IEEE. http://dx.doi.org/10.1109/LINDI.2011.6031124
   Google Scholar
• Kofler, M., Beham, A., Wagner, S., & Affenzeller, M. (2014). Affinity based slotting in warehouses with dynamic order patterns. Advanced methods and applications in computational intelligence, 123–143.
   Google Scholar
• Koster, K. (2001b). Routing order pickers in a warehouse with a middle aisle. European Journal of Operational Research, 133(1), 32–43. https://doi.org/10.1016/S0377-2217(00)00177-6
   Web of Science ®Google Scholar
• Koster, K. J. (2001a). Routing methods for warehouses with multiple cross aisles. International Journal of Production Research, 39(9), 1865–1883. https://doi.org/10.1080/00207540110028128
   Web of Science ®Google Scholar
• Koster, R.., Le-Duc, T., & Roodbergen, K. J. (2007). Design and control of warehouse order picking: A literature review. European Journal of Operational Research, 182(2), 481–501. https://doi.org/10.1016/j.ejor.2006.07.009
   Web of Science ®Google Scholar
• Kovács, András. (2011). Optimizing the storage assignment in a warehouse served by milkrun logistics. International Journal of Production Economics, 133(1), 312–318. http://dx.doi.org/10.1016/j.ijpe.2009.10.028
   Web of Science ®Google Scholar
• Kress, Dominik, Boysen, Nils, & Pesch, Erwin. (2017). Which items should be stored together? A basic partition problem to assign storage space in group-based storage systems. IISE Transactions, 49(1), 13–30. http://dx.doi.org/10.1080/0740817X.2016.1213469
   Web of Science ®Google Scholar
• Kumar, S., Narkhede, B. E., & Jain, K. (2021). Revisiting the warehouse research through an evolutionary lens: A review from 1990 to 2019. International Journal of Production Research, 59(11), 3470–3492. https://doi.org/10.1080/00207543.2020.1867923
   Web of Science ®Google Scholar
• Kumar, V., George, M., & Pancras, J. (2008). Cross-buying in retailing: Drivers and consequences. Journal of Retailing, 84(1), 15–27. https://doi.org/10.1016/j.jretai.2008.01.007
   Web of Science ®Google Scholar
• Kuo, R. J., Kuo, P. H., Chen, Y. R., & Zulvia, F. E. (2016). Application of metaheuristics-based clustering algorithm to item assignment in a synchronized zone order picking system. Applied Soft Computing, 46, 143–150. https://doi.org/10.1016/j.asoc.2016.03.012
   Web of Science ®Google Scholar
• Kyriakidis, E. G., & Dimitrakos, T. D. (2019). Stochastic single vehicle routing problem with ordered customers and partial fulfilment of demands. International Journal of Systems Science: Operations & Logistics, 6(3), 285–299. https://doi.org/10.1080/23302674.2017.1381888
   Google Scholar
• Lanza, Giacomo, Passacantando, Mauro, & Scutellà, Maria Grazia. (2022). Assigning and sequencing storage locations under a two level storage policy: Optimization model and matheuristic approaches. Omega, 108, 102565. http://dx.doi.org/10.1016/j.omega.2021.102565
   Web of Science ®Google Scholar
• Larranaga, P., Kuijpers, C. M. H., Murga, R. H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13(2), 129–170. https://doi.org/10.1023/A:1006529012972
   Web of Science ®Google Scholar
• Li, J., Huang, R., & Dai, J. B. (2017). Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China. International Journal of Production Research, 55(2), 447–461. https://doi.org/10.1080/00207543.2016.1187313
   Web of Science ®Google Scholar
• Li, Xiaowei, Hua, Guowei, Huang, Anqiang, Sheu, Jiuh-Biing, Cheng, T.C.E, & Huang, Fengquan. (2020). Storage assignment policy with awareness of energy consumption in the Kiva mobile fulfilment system. Transportation Research Part E: Logistics and Transportation Review, 144, 102158. http://dx.doi.org/10.1016/j.tre.2020.102158
   Web of Science ®Google Scholar
• Li, Xinyu, & Gao, Liang. (2016). An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem. International Journal of Production Economics, 174, 93–110. http://dx.doi.org/10.1016/j.ijpe.2016.01.016
   Web of Science ®Google Scholar
• Lin, L., Gen, M., & Wang, X. (2009). Integrated multistage logistics network design by using hybrid evolutionary algorithm. Computers & Industrial Engineering, 56(3), 854–873. https://doi.org/10.1016/j.cie.2008.09.037
   Web of Science ®Google Scholar
• Liu, C.-M. (2004). Optimal storage layout and order picking for warehousing. International Journal of Operations Research, 1, 37–46.
   Google Scholar
• Liu, H., & Sese, F. J. (2022). The impact of mobile app adoption on cross-buying: The moderating roles of product category characteristics and adoption timing. Journal of Retailing, 98(2), 241–259. https://doi.org/10.1016/j.jretai.2021.02.002
   Web of Science ®Google Scholar
• Meneghetti, Antonella, & Monti, Luca. (2011). Sustainable storage assignment and dwell-point policies for automated storage and retrieval systems. Production Planning & Control, 24(6), 511–520. http://dx.doi.org/10.1080/09537287.2011.637525
   Web of Science ®Google Scholar
• Meneghetti, Antonella, & Monti, Luca. (2013). Multiple-weight unit load storage assignment strategies for energy-efficient automated warehouses. International Journal of Logistics Research and Applications, 17(4), 304–322. http://dx.doi.org/10.1080/13675567.2013.861896
   Web of Science ®Google Scholar
• Mirzaei, M., Zaerpour, N., & De Koster, R. (2021b). The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance. Transportation Research Part E: Logistics and Transportation Review, 146, 102207. https://doi.org/10.1016/j.tre.2020.102207
   Web of Science ®Google Scholar
• Mirzaei, M., Zaerpour, N., & de Koster, R. B. (2021a). How to benefit from order data: Correlated dispersed storage assignment in robotic warehouses. International Journal of Production Research, 1–20. https://doi.org/10.1080/00207543.2021.1971787
   Web of Science ®Google Scholar
• Mondal, R., Das, S., Das, S. C., Shaikh, A. A., & Bhunia, A. K. (2022). Pricing strategies and advance payment-based inventory model with partially backlogged shortages under interval uncertainty. International Journal of Systems Science: Operations & Logistics, 1–25. https://doi.org/10.1080/23302674.2022.2070296
   Google Scholar
• Muharni, Y., & Khoirunnisa, M. (2019). Warehouse layout designing of slab using dedicated storage and particle swarm optimization. In IOP Conference Series: Materials Science and Engineering (Vol. 532, No.1, p. 012003). IOP Publishing.
   Google Scholar
• Muppani, V., & Adil, G. (2008). Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach. Omega, 36(4), 609–618. https://doi.org/10.1016/j.omega.2007.01.006
   Web of Science ®Google Scholar
• Nguyen, D. H., de Leeuw, S., & Dullaert, W. E. H. (2018). Consumer behaviour and order fulfilment in online retailing: A systematic review. International Journal of Management Reviews, 20(2), 255–276. https://doi.org/10.1111/ijmr.12129
   Web of Science ®Google Scholar
• Öncan, Temel, & Cağırıcı, Merve. (2013). MILP Formulations for the Order Batching Problem in Low-Level Picker-to-Part Warehouse Systems. IFAC Proceedings Volumes, 46(9), 471–476. http://dx.doi.org/10.3182/20130619-3-RU-3018.00372
   Google Scholar
• Padmanabhan, B., & Tuzhilin, A. (1999). Unexpectedness as a measure of interestingness in knowledge discovery. Decision Support Systems, 27(3), 303–318. https://doi.org/10.1016/S0167-9236(99)00053-6
   Web of Science ®Google Scholar
• Pan, D., Zhang, H., Chen, W., & Lu, K.. (2015). Transmission of multimedia contents in opportunistic networks with social selfish nodes. Multimedia Systems, 21, 277–288.
   Web of Science ®Google Scholar
• Pan, J. C. H., Shih, P. H., & Wu, M. H. (2012). Storage assignment problem with travel distance and blocking considerations for a picker-to-part order picking system. Computers & Industrial Engineering, 62(2), 527–535. https://doi.org/10.1016/j.cie.2011.11.001
   Web of Science ®Google Scholar
• Pang, K. W., & Chan, H. L. (2017). Data mining-based algorithm for storage location assignment in a randomised warehouse. International Journal of Production Research, 55(14), 4035–4052. https://doi.org/10.1080/00207543.2016.1244615
   Web of Science ®Google Scholar
• Pourhassan, M. R., & Raissi, S. (2017). An integrated simulation-based optimization technique for multi-objective dynamic facility layout problem. Journal of Industrial Information Integration, 8, 49–58. https://doi.org/10.1016/j.jii.2017.06.001
   Web of Science ®Google Scholar
• Qin, Kaida, Chen, Frank Youhua, & Ma, Lijun. (2014). Cutting down the travel distance of put systems at Kunming International Flower Auction Market. International Journal of Production Research, 53(12), 3573–3585. http://dx.doi.org/10.1080/00207543.2014.980013
   Web of Science ®Google Scholar
• Quintanilla, Sacramento, Pérez, Ángeles, Ballestín, Francisco, & Lino, Pilar. (2014). Heuristic algorithms for a storage location assignment problem in a chaotic warehouse. Engineering Optimization, 47(10), 1405–1422. http://dx.doi.org/10.1080/0305215X.2014.969727
   Web of Science ®Google Scholar
• Rahmouni, M., Hennet, J. C., & Fnaiech, F. (2015). Multi-product joint delivery planning in a retailers’ network under resource constraints. International Journal of Systems Science: Operations & Logistics, 2(3), 125–134. https://doi.org/10.1080/23302674.2014.998315
   Google Scholar
• Ramtin, Faraz, & Pazour, Jennifer A. (2015). Product allocation problem for an AS/RS with multiple in-the-aisle pick positions. IIE Transactions, 47(12), 1379–1396. http://dx.doi.org/10.1080/0740817X.2015.1027458
   Web of Science ®Google Scholar
• Rao, Subir S, & Adil, Gajendra K.. (2013). Class-based storage with exact S-shaped traversal routeing in low-level picker-to-part systems. International Journal of Production Research, 51(16), 4979–4996. http://dx.doi.org/10.1080/00207543.2013.784419
   Web of Science ®Google Scholar
• Rao, Subir S, & Adil, Gajendra K.. (2017). Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses. International Journal of Production Research, 55(2), 327–346. http://dx.doi.org/10.1080/00207543.2016.1158428
   Web of Science ®Google Scholar
• Ratliff, H. D., & Rosenthal, A. S. (1983). Order-picking in a rectangular warehouse: A solvable case of the traveling salesman problem. Operations Research, 31(3), 507–521. https://doi.org/10.1287/opre.31.3.507
   Web of Science ®Google Scholar
• Reyes, J. J. R., Solano-Charris, E. L., & Montoya-Torres, J. R. (2019). The storage location assignment problem: A literature review. International Journal of Industrial Engineering Computations, 10, 199–224. https://doi.org/10.5267/j.ijiec.2018.8.001
   Web of Science ®Google Scholar
• Rodrigues, T. F. O., Dantas, M. M., & Cavalcante, C. A. V. (2020). A dynamic inventory rationing policy for business-to-consumer e-tail stores in a supply disruption context. Computers & Industrial Engineering, 142, 106379. https://doi.org/10.1016/j.cie.2020.106379
   Web of Science ®Google Scholar
• Rong, Z., Wang, Q., & Zhang, H. (2023). Effects of cross-platform multichannel shopping on online customer–firm relationship length, depth, and breadth: An empirical investigation. Information Processing & Management, 60(2), 103218. https://doi.org/10.1016/j.ipm.2022.103218
   Web of Science ®Google Scholar
• Roodbergen, Kees Jan, & de Koster, René. (2001). Routing order pickers in a warehouse with a middle aisle. European Journal of Operational Research, 133(1), 32–43. http://dx.doi.org/10.1016/S0377-2217(00)00177-6
   Web of Science ®Google Scholar
• Roodbergen, K. J., Vis, I. F., & Taylor, G. D., Jr. (2015). Simultaneous determination of warehouse layout and control policies. International Journal of Production Research, 53(11), 3306–3326. https://doi.org/10.1080/00207543.2014.978029
   Web of Science ®Google Scholar
• Rosenblatt, M. J., & Roll, Y. (1984). Warehouse design with storage policy considerations. International Journal of Production Research, 22(5), 809–821. https://doi.org/10.1080/00207548408942501
   Web of Science ®Google Scholar
• Rossit, D. A., Tohmé, F., & Frutos, M. (2019). A data-driven scheduling approach to smart manufacturing. Journal of Industrial Information Integration, 15, 69–79. https://doi.org/10.1016/j.jii.2019.04.003
   Web of Science ®Google Scholar
• Saber, A. Y., & Khandelwal, T. (2017, March). IoT based online load forecasting. In 2017 Ninth Annual IEEE Green Technologies Conference (GreenTech) (pp. 189–194). IEEE.
   Google Scholar
• Septiani, W., Divia, G. A., & Adisuwiryo, S. (2020). Warehouse layout designing of cable manufacturing company using dedicated storage and simulation promodel. In IOP Conference Series: Materials Science and Engineering (Vol. 847, No. 1, p. 012054). IOP Publishing.
   Google Scholar
• Sheen, G. J., Nguyen, A. H., & Yeh, Y. (2022). Category management under non-symmetric demands. International Journal of Systems Science: Operations & Logistics, 9(4), 569–596.
   Google Scholar
• Singbal, Vishwesh, & Adil, Gajendra K. (2021). Designing an automated storage/retrieval system with a single aisle-mobile crane under three new turnover based storage policies. International Journal of Computer Integrated Manufacturing, 34(2), 212–226. http://dx.doi.org/10.1080/0951192X.2021.1872104
   Web of Science ®Google Scholar
• Srikant, R. (1994, September 12–15). Fast algorithms for mining association rules. In VLDB’94, Proceedings of 20th International Conference on Very Large Data Bases, Santiago de Chile, Chile.
   Google Scholar
• Swami, R. (1993, May 26–28). Mining association rules between sets of items in large databases. In 1993 ACM SIGMOD International Conference on Management of Data, Washington DC, USA.
   Google Scholar
• Tompkins, M. F. (2003). Optimization techniques for task allocation and scheduling in distributed multi-agent operations [Doctoral dissertation]. Massachusetts Institute of Technology. https://dspace.mit.edu/handle/1721.1/16974
   Google Scholar
• University of California, Irvine. (2015). Dateset. https://archive.ics.uci.edu/ml/datasets/Online+Retail
   Google Scholar
• Van Gils, T., Ramaekers, K., Caris, A., & De Koster, R. B. (2018). Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review. European Journal of Operational Research, 267(1), 1–15. https://doi.org/10.1016/j.ejor.2017.09.002
   Web of Science ®Google Scholar
• Van Oudheusden, D. L., & Zhu, W. (1992). Storage layout of AS/RS racks based on recurrent orders. European Journal of Operational Research, 58(1), 48–56. https://doi.org/10.1016/0377-2217(92)90234-Z
   Web of Science ®Google Scholar
• Vaziri, S., Zaretalab, A., Esmaeili, M., & Niaki, S. T. A. (2018). An integrated production and procurement design for a multi-period multi-product manufacturing system with machine assignment and warehouse constraint. Applied Soft Computing, 70, 238–262. https://doi.org/10.1016/j.asoc.2018.05.037
   Web of Science ®Google Scholar
• Walter, Rico, Boysen, Nils, & Scholl, Armin. (2013). The discrete forward–reserve problem – Allocating space, selecting products, and area sizing in forward order picking. European Journal of Operational Research, 229(3), 585–594. http://dx.doi.org/10.1016/j.ejor.2013.02.047
   Web of Science ®Google Scholar
• Wang, Q. (2023, January). Application of machine learning algorithm in marketing education. In Application of Big Data, Blockchain, and Internet of Things for Education Informatization: Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29–31, 2022, Proceedings, Part I (pp. 326–335). Springer Nature Switzerland.
   Google Scholar
• Wang, Yanyan, Liu, Ziwei, Huang, Ke, Mou, Shandong, & Zhang, Rongxu. (2020). Model and solution approaches for retrieval operations in a multi-tier shuttle warehouse system. Computers & Industrial Engineering, 141, 106283. http://dx.doi.org/10.1016/j.cie.2020.106283
   Web of Science ®Google Scholar
• Weidinger, F., & Boysen, N. (2018). Scattered storage: How to distribute stock keeping units all around a mixed-shelves warehouse. Transportation Science, 52(6), 1412–1427. https://doi.org/10.1287/trsc.2017.0779
   Web of Science ®Google Scholar
• Winkelhaus, S., Grosse, E. H., & Morana, S. (2021). Towards a conceptualisation of Order Picking 4.0. Computers & Industrial Engineering, 159, 107511. https://doi.org/10.1016/j.cie.2021.107511
   Web of Science ®Google Scholar
• Wutthisirisart, Phichet, Noble, James S, & Alec Chang, C.. (2015). A two-phased heuristic for relation-based item location. Computers & Industrial Engineering, 82, 94–102. http://dx.doi.org/10.1016/j.cie.2015.01.020
   Web of Science ®Google Scholar
• Xiao, J., & Zheng, L. (2010). A correlated storage location assignment problem in a singleblock-multi-aisles warehouse considering BOM information. International Journal of Production Research, 48(5), 1321–1338. https://doi.org/10.1080/00207540802555736
   Web of Science ®Google Scholar
• Yan, L. (2023, January). Application of data mining in psychological education of college students in private independent colleges. In Application of Big Data, Blockchain, and Internet of Things for Education Informatization: Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29–31, 2022, Proceedings, Part I (pp. 206–215). Springer Nature Switzerland.
   Google Scholar
• Yang, P., Peng, Y., Ye, B., & Miao, L. (2017). Integrated optimization of location assignment and sequencing in multi-shuttle automated storage and retrieval systems under modified 2n-command cycle pattern. Engineering Optimization, 49(9), 1604–1620. https://doi.org/10.1080/0305215X.2016.1261128
   Web of Science ®Google Scholar
• Young, J. (2022). US ecommerce grows 10.8% in Q3 2022. Digital Commerce360. https://www.digitalcommerce360.com/article/us-ecommerce-sales/.
   Google Scholar
• Yu, Yugang, & de Koster, René B.M. (2013). On the suboptimality of full turnover-based storage. International Journal of Production Research, 51(6), 1635–1647. http://dx.doi.org/10.1080/00207543.2011.654012
   Web of Science ®Google Scholar
• Zaerpour, Nima, de Koster, René B.M, & Yu, Yugang. (2013). Storage policies and optimal shape of a storage system. International Journal of Production Research, 51(23-24), 6891–6899. http://dx.doi.org/10.1080/00207543.2013.774502
   Web of Science ®Google Scholar
• Zak, M. J., Parthasarathy, S., Ogihara, M., & Li, W. (1997). New algorithms for fast discovery of association rules. In 3rd Intl. Conf. on Knowledge Discovery and Data Mining, 283–286.
   Google Scholar
• 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, 234, 108058. http://dx.doi.org/10.1016/j.ijpe.2021.108058
   Web of Science ®Google Scholar
• Zhang, J., Wang, X., Chan, F. T., & Ruan, J. (2017). On-line order batching and sequencing problem with multiple pickers: A hybrid rule-based algorithm. Applied Mathematical Modelling, 45, 271–284. https://doi.org/10.1016/j.apm.2016.12.012
   Web of Science ®Google Scholar
• Zhang, R.-Q., Wang, M., & Pan, X. (2019). New model of the storage location assignment problem considering demand correlation pattern. Computers & Industrial Engineering, 129, 210–219. https://doi.org/10.1016/j.cie.2019.01.027
   Web of Science ®Google Scholar
• Zhou, L., Sun, L., Li, Z., Li, W., Cao, N., & Higgs, R. (2018). Study on a storage location strategy based on clustering and association algorithms. Soft Computing, https://doi.org/10.1007/s00500-00018-03702-00509
   Google Scholar