A bi-level optimization model for grouping constrained storage location assignment problems

Xie, J, Mei, Y, Ernst, A, Li, X and Song, A 2018, 'A bi-level optimization model for grouping constrained storage location assignment problems', IEEE Transactions on Cybernetics, vol. 48, no. 1, pp. 385-398.

Document type: Journal Article
Collection: Journal Articles

Title A bi-level optimization model for grouping constrained storage location assignment problems
Author(s) Xie, J
Mei, Y
Ernst, A
Li, X
Song, A
Year 2018
Journal name IEEE Transactions on Cybernetics
Volume number 48
Issue number 1
Start page 385
End page 398
Total pages 14
Publisher IEEE
Abstract In this paper, a novel bi-level grouping optimization (BIGO) model is proposed for solving the storage location assignment problem with grouping constraint (SLAP-GC). A major challenge in this problem is the grouping constraint which restricts the number of groups each product can have and the locations of items in the same group. In SLAP-GC, the problem consists of two subproblems, one is how to group the items, and the other one is how to assign the groups to locations. It is an arduous task to solve the two subproblems simultaneously. To overcome this difficulty, we propose a BIGO. BIGO optimizes item grouping in the upper level, and uses the lower-level optimization to evaluate each item grouping. Sophisticated fitness evaluation and search operators are designed for both upper and lower level optimization so that the feasibility of solutions can be guaranteed, and the search can focus on promising areas in the search space. Based on the BIGO model, a multistart random search method and a tabu algorithm are proposed. The experimental results on the real-world dataset validate the efficacy of the BIGO model and the advantage of the tabu method over the random search method.
Subject Operations Research
Artificial Intelligence and Image Processing not elsewhere classified
Keyword(s) Grouping constraint (GC)
storage location assignment problem
tabu search
DOI - identifier 10.1109/TCYB.2016.2638820
Copyright notice © 2016 IEEE
ISSN 2168-2267
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