A relax-and-fix method for clothes inventory balancing scheduling problem

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.

Keywords:

• Fast-fashion apparel industry
• clothes inventory balancing scheduling problem
• lateral transshipment
• relax-and-fix
• heuristics
• mixed integer linear programming

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available at the link https://pan.baidu.com/s/1LdALYq79t4Nd6rZ0XxXvBA, with the retrieve code: f61r.

Additional information

Funding

The authors thank the editors and the anonymous referees for many useful suggestions and comments, which greatly improves the paper. This work was supported by the National Natural Science Foundation of China (NSFC) under Grant 71971155 and by the Fundamental Research Funds for the Central Universities. The work was also supported by Natural Science Foundation of Shanghai (No 18ZR1413200).

Notes on contributors

Shijin Wang

Shijin Wang, received the B.Eng. degree from the Department of Industrial Engineering, Zhejiang University of Technology, Zhejiang, China, in 2002; and the Ph.D. degree from the Department of Industrial Engineering and Management, Shanghai Jiaotong University, Shanghai, China, 2009. From 2009-Present, he worked as associate professor at the Department of Management Science & Engineering, School of Economics & Management, Tongji University, Shanghai, China. His current research interests include combinatorial optimization, production scheduling, artificial intelligence-based algorithms, and supply chain optimization.

Hanyu Zhang

Hanyu Zhang is a PhD student in Management Science and Engineering from the School of Economics and Management, Tongji University, China. Her research interests are scheduling, integer programming and combinatorial optimization.

Feng Chu

Feng Chu received the B.S. degree in electrical engineering from Hefei University of Technology, Hefei, China, in 1986; the M.S. degree in metrology, automatic control, and electrical engineering from National Polytechnic Institute of Lorraine, Lorraine, France, in 1991; and the Ph.D. degree in automatic control, computer science, and production management from University of Metz, Metz, France, in 1995. Feng Chu is currently a Full Professor of Operations Research at Univ Evry, University of Paris Saclay, Evry, France and leader of the AROBAS research team of the IBISC Lab. Her research interests include combinatorial optimization, operations research, stochastic programming and Petri nets for modeling, analysis, and optimization of complex systems, such as intelligent transportation systems and logistic and production. She is the author/co-author of more than 120 papers in international journals. She is awarded by the French ministry of Education for her Doctoral Supervision and Research Activities (PEDR) since 2005. She was selected for Foreign Hundred Talents Program of Anhui province in 2013, Thousand Talents Program of Sichuan province in 2016 and Min Jian Scholar in Fujian province of Chine, 2018. Dr. Chu was an Associate Editor for IEEE T-SMC, Part C from 2010 to 2013. She is currently an Associate Editor for IEEE T-ITS and IEEE TASE, an Guest Editor for IJPR, TRC and JOCO. She is an IPC member for over 80 international conferences.

Li Yu

Li Yu, received the B.Eng. degree from the Department of Mechanical Electronic Engineering, East China University of Science and Technology, Shanghai, China; and received his Ph.D. degree from the Department of Industrial Engineering and Management at Shanghai Jiaotong University, Shanghai, China, 2009. He is an associate research fellow at Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance & Economics, Shanghai, China. His research interests include supply chain management, mass customization, credit risk evaluation and data mining.