Abstract
This article defines a new dynamic storage assignment problem (DSAP) and develops an integrated mechanism for optimization purpose, based on the ABC classification and mutual affinity of products. A product affinity-based heuristic (PABH)—a technique based on data mining—is developed for calculation of pairwise relationships between products. It is shown that the analytical and multi-parametric DSAP is a quadratic assignment problem (QAP) and thus non-deterministic polynomial-time (NP)-hard. A greedy genetic algorithm (GA) is therefore developed for handling the computational complexity of the DSAP. Performance comparisons between the new approach and the traditional ABC classification method are conducted. The experimental results show that a preferred storage assignment approach is to simultaneously maximize the sum of affinity values and the product of zone indicators and order frequencies based on traditional ABC classification. The experiments on a distribution center of a family care product manufacturer indicate 7.14 to 104.48 % improvement in the average order picking time.
Similar content being viewed by others
References
Renaud J, Ruiz A (2007) Improving product location and order picking activities in a distribution centre. J Oper Res Soc 59(12):1603–1613
van den Berg JP (1999) A literature survey on planning and control of warehousing systems. IIE Trans 31(8):751–762
Rouwenhorst B, Reuter B, Stockrahm V, van Houtum G, Mantel R, Zijm W (2000) Warehouse design and control: framework and literature review. Eur J Oper Res 122(3):515–533
De Koster R, Le-Duc T, Roodbergen KJ (2007) Design and control of warehouse order picking: a literature review. Eur J Oper Res 182(2):481–501
Li J (2015). Dynamic storage planning and control in a warehouse with robotic equipment. Master’s Thesis. School of Industrial Engineering, Purdue University
Bartholdi JJ, Gue KR (2000) Reducing labor costs in an LTL crossdocking terminal. Oper Res 48(6):823–832
Hopp WJ, Spearman ML (2008) Factory physics: foundations of manufacturing management, 3rd edn. Chicago, Waveland, p 720
Gallego G, Queyranne M, Simchi-Levi D (1996) Single resource multi-item inventory systems. Oper Res 44(4):580–595
Hariga MA, Jackson PL (1996) The warehouse scheduling problem: Formulation and algorithms. IIE Trans 28:115–127
Tersine RJ (1994) Principles of inventory and materials management. Prentice-Hall International edition, in English -4th Ed
Hausman WH, Schwarz LB, Graves SC (1976) Optimal storage assignment in automatic warehouse systems. Manag Sci 22(6):629–638
Larson TN, March H, Kusiak A (1997) A heuristic approach to warehouse layout with class-based storage. IIE Trans 29(4):337–348
Muppani VR, Adil GK (2008) A branch and bound algorithm for class based storage location assignment. Eur J Oper Res 189(2):492–507
Gamberini R, Grassi A, Mora C, Rimini B (2008) An innovative approach for optimizing warehouse capacity utilization. Int J Logist 11:137–165
Gu J, Goetschalckx M, McGinnis LF (2007) Research on warehouse operation: a comprehensive review. Eur J Oper Res 177(1):1–21
Lolli F, Ishizaka A, Gamberini R (2014) New AHP-based approaches for multi-criteria inventory classification. Int J Prod Econ 156:62–74
Nof SY, Drezner Z (1986) Part flow in the robotic assembly plan problem. Robot Mater Flow 3(1-3):197–205
Drezner Z, Nof SY (1984) On optimizing bin picking and insertion plans for assembly robots. IIE Trans 16(3):262–270
Han J, Kamber M (2006) Data mining concepts and techniques (2nd ed., p. 772)
Srikant R, Agrawal R (1997) Mining generalized association rules. Futur Gener Comput Syst 13:161–180
Chen M-C, Huang C-L, Chen K-Y, Wu H-P (2005) Aggregation of orders in distribution centers using data mining. Expert Syst Appl 28(3):453–460
Chiang DM-H, Lin C-P, Chen M-C (2011) The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres. Enterp Inf Syst 5(2):219–234
Chuang Y-F, Lee H-T, Lai Y-C (2012) Item-associated cluster assignment model on storage allocation problems. Comput Ind Eng 63(4):1171–1177
Chiang DM-H, Lin C-P, Chen M-C (2012) Data mining based storage assignment heuristics for travel distance reduction. Expert Syst 31(1):81–90
Shani S, Gonzalez T (1976) P-complete approximation problems. J ACM 23:555–565
Taillard ED (1995) Comparison of iterative searches for the quadratic assignment problem. Locat Sci 3(2):87–105
Christofides N, Benavent E (1989) An exact algorithm for the quadratic assignment problem on a tree. Oper Res 37(5):760–768
Burkard R, Dell’Amico M, Martello S (2009) Assignment problems, revised reprint. SIAM, ISBN 978-1-611972-22-1
Gambardella LM, Taillard ED, Dorigo M (1999) Ant colonies for the quadratic assignment problem. J Oper Res Soc 50:167–176
Maniezzo V, Colorni A (1999) The ant system applied to the quadratic assignment problem. IEEE Trans Knowl Data Eng 11(5):769–778
Talbi E-G, Roux O, Fonlupt C, Robillard D (2001) Parallel ant colonies for the quadratic assignment problem. Futur Gener Comput Syst 17:441–449
Ahuja RK, Orlin JB, Tiwari A (2000) A greedy genetic algorithm for the quadratic assignment problem. Comput Oper Res 27:917–934
Drezner Z (2003) A new genetic algorithm for the quadratic assignment problem. INFORMS J Comput 15(3):320–330
Drezner Z (2008) Extensive experiments with hybrid genetic algorithms for the solution of the quadratic assignment problem. Comput Oper Res 35:717–736
Zhang GQ et al (2002) A class of genetic algorithms for multiple-level warehouse layout problems. Int J Prod Res 40(3):731–744
Li M, Tang H (2009) An improved genetic algorithm for locations allocation optimization problem of automated warehouse. Adv Intell Soft Comput 62:1549–1560
Glover F (1994) Genetic algorithms and scatter search: unsuspected potential. Stat Comput 4:131–40
Li T, Pardalos PM, Wolkowicz H (1994) A greedy randomized adaptive search procedure for the quadratic assignment problem. DIMACS series in discrete mathematics and theoretical computer science 237–261
Moghaddam M, Nof SY (2015) Best matching with interdependent preferences—implications for capacitated cluster formation and evolution. Decis Support Syst. doi:10.1016/j.dss.2015.08. 005
Nof SY, Ceroni J, Jeong W, Moghaddam M (2015) Revolutionizing collaboration through e-work, e-business, and e-service. Springer, ISBN 978-3-662-45777-1
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, J., Moghaddam, M. & Nof, S.Y. Dynamic storage assignment with product affinity and ABC classification—a case study. Int J Adv Manuf Technol 84, 2179–2194 (2016). https://doi.org/10.1007/s00170-015-7806-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-015-7806-7