Solving Production Scheduling Problems Using a Local Search Metaheuristic in Comparison with the Earliest Due Date Rule: A Case Study of the Cosmetics Industry

Abstract

This study presents a production scheduling approach for the cosmetic products industry by focusing on the application of a Local Search metaheuristic to determine effective production sequences under practical manufacturing constraints. Production scheduling is a highly complex problem in operations research because the number of possible job sequences increases rapidly as the problem size becomes larger. As a result, exact optimization approaches may require substantial computational effort, particularly for practical industrial cases. Therefore, this study applies a Local Search method combined with the Earliest Due Date rule to compare and identify effective solutions for different case study sizes obtained from cosmetic production data. The main performance measure is the total cost of all jobs in the system, with the objective of minimizing the overall production scheduling cost. The experimental results indicate that the Local Search approach can provide effective solutions for reducing total cost and is suitable for addressing complex production scheduling problems with multiple practical constraints in industrial applications.