A matheuristic approach for solving a simultaneous lot sizing and scheduling problem with client prioritization in tire industry. (March 2022)

• Record Type: Journal Article
• Authors: Koch, Cyril; Arbaoui, Taha; Ouazene, Yassine; Yalaoui, Farouk; De Brunier, Humbert; Jaunet, Nicolas; De Wulf, Antoine
• Is Part Of: Computers & industrial engineering. Volume 165(2022)
• Publication Date: 2022-03
• Subjects: Tire industry -- Lot Sizing and Scheduling problem -- Customer prioritization -- Mathematical Programming -- Matheuristic Approach; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.107932
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A real-world problem in tire industry is tackled. Specific constraints such as customer prioritization are presented. A MIP formulation and a decomposition-based matheuristic are proposed. Several objectives related to inventory and service level are considered. A sensitivity analysis of eligibility constraint is conducted. Abstract: This paper introduces an integrated lot sizing and scheduling problem inspired from a real-world application in off-the-road tire industry. This problem considers the assignment of different items on parallel machines with complex eligibility constraints within a finite planning horizon. It also considers a large panel of specific constraints such as: backordering, a limited number of setups, upstream resources saturation and customers prioritization. A novel mixed integer formulation is proposed with the objective of optimizing different normalized criteria related to the inventory and service level performance. Based on this mathematical formulation, a problem-based matheuristic method that solves the lot sizing and assignment problems separately is proposed to solve the industrial case. A computational study and sensitivity analysis are carried out based on real-world data with up to 170 products, 70 unrelated parallel machines and 42 periods. The obtained results show the effectiveness of the proposed approach on improving the company's solution. Indeed, the two most important KPIs for the management have been optimized of respectively 32% for the backorders and 13% for the overstock. Moreover, the computational time have been reduced significantly.