Xie 2018 Bi-level optimization model for grouping contrained.pdf (448.46 kB)

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

Download (448.46 kB)
journal contribution
posted on 30.03.2021, 00:00 by Jing Xie, Yi Mei, Andreas T Ernst, Xiaodong Li, Andy Song
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 search algorithm are proposed. The experimental results on the real-world dataset validate the efficacy of the BIGO model and the advantage of the tabu search method over the random search method. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

History

Preferred citation

Xie, J., Mei, Y., Ernst, A. T., Li, X. & Song, A. (2018). A bi-level optimization model for grouping constrained storage location assignment problems. IEEE Transactions on Cybernetics, 48(1), 385-398. https://doi.org/10.1109/TCYB.2016.2638820

Journal title

IEEE Transactions on Cybernetics

Volume

48

Issue

1

Publication date

01/01/2018

Pagination

385-398

Publisher

IEEE

Publication status

Published

Contribution type

Article

ISSN

2168-2267

eISSN

2168-2275

Article number

1

Language

en

Exports