Scheduling challenges in multi-line garment production: Application to an Algerian case study

This paper investigates a novel scheduling problem within the textile industry integrating multiple aspects such as dedicated multi-line flow shops, lot streaming and heterogeneous workforce assignment with the objective to minimize the makespan. To address the problem, the proposed methodology consists in developing a Mixed Integer Linear Programming (MILP) formulation as a benchmark. Additionally, an Enhanced Genetic Algorithm (EGA) is developed to generate high-quality solutions to large-size instances in reasonable time. The study is anchored in a case study of a leading Algerian textile company. A computational study was conducted on a set of industrial and artificial instances. The EGA’s performance was assessed using both cases. The results underscore the EGA’s effectiveness in delivering high-quality solutions, confirming its suitability for practical, real-world applications and offering valuable insights.