A Mixed Integer Programming model to optimize production planning in the luxury textile industry

• Published in: Procedia computer science Vol. 253; pp. 1175 - 1184
• Main Authors: Rossi, Andrea, Tiacci, Lorenzo, Simonetti, Matteo
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2025
• Subjects: MIP; production planning; scheduling; textile industry; scheduling; production planning; textile industry; MIP
• ISSN: 1877-0509; 1877-0509
• DOI: 10.1016/j.procs.2025.01.179

The fashion clothing apparel sector operates in a dynamic environment, subject to seasonal changes in the collection. There are at least two collection every year, consisting in tight windows for production. Moreover, the collection of the orders happens in the sales campaign, so the time allotted for production is low and it is important to optimize the production planning. Furthermore, in the textile industry, companies often resort to a subcontracting network to carry out production. The present work tackles the fully fashioned knitwear production process, typical of the luxury industry, with the objective of optimizing the production planning. A novel Mixed Integer Programming (MIP) to address the scheduling for a multi-stage, multi-site production system with batch processing is presented with the objective of minimizing both the makespan and the number of models that are assigned to a different manufacturer than the one who realized their samples during the prototyping and sampling phase. The proposed model can both operate as a scheduler and as decision support tool. To validate the effectiveness of the model an experiment is conducted utilizing real production data of a fashion company and comparing the result obtained with the operative planning adopted by the company. Results consist in a reduction of the production makespan and in a better assignment of item to manufacturers, representing a great improvement from the company scheduling.