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author:

Wang, Shijin (Wang, Shijin.) [1] | Zhang, Hanyu (Zhang, Hanyu.) [2] | Chu, Feng (Chu, Feng.) [3] | Yu, Li (Yu, Li.) [4]

Indexed by:

EI

Abstract:

The clothes inventory balancing scheduling problem (CIBSP) among branch stores with the allowance of lateral transshipments has gained increasing attentions in fast-fashion apparel industry, especially for the trial sale of new products. To solve the CIBSP faced by a leading apparel company in China, a mixed integer linear programming (MILP) model is first formulated, based on which a relax-and-fix (R&F) method is developed. Several heuristic cuts based on practical experience and observations are further integrated into the R&F method to speed up the searching. The effectiveness of the method is demonstrated through extensive computational experiments: it is able to provide near-optimal solutions with average optimality gap 1.15% with less computation time, compared to solving the MILP model directly in a commercial solver. Case studies also demonstrate that the developed R&F method can obtain high-quality solutions with average optimality gap 0.09% with much less computation time. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Keyword:

Balancing Heuristic methods Integer programming Scheduling

Community:

  • [ 1 ] [Wang, Shijin]School of Economics and Management, Tongji University, Shanghai, China
  • [ 2 ] [Zhang, Hanyu]School of Economics and Management, Tongji University, Shanghai, China
  • [ 3 ] [Chu, Feng]Laboratoire IBISC, Univ-Évry, Université Paris-Saclay, Évry, France
  • [ 4 ] [Chu, Feng]School of Economics and Management, Fuzhou University, Fuzhou, China
  • [ 5 ] [Yu, Li]Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, Shanghai, China

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Source :

International Journal of Production Research

ISSN: 0020-7543

Year: 2023

Issue: 20

Volume: 61

Page: 7085-7104

7 . 0

JCR@2023

7 . 0 0 0

JCR@2023

ESI HC Threshold:35

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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