Comparison of two Meta-Heuristics for the Bi-Objective Flexible Job Shop Scheduling Problem with Sequence Dependent Setup Times

Abstract

The increasingly competitivity in the plastic container market is driving companies toward a greater focus on efficiency, and mass production customisation, which triggers the increase of productivity by implementing more efficient and faster IT solutions. This work is based on a Portuguese case study, to develop a scheduling model considering the specific characteristics of this type of facilities and increase its competitiveness. To this end, two different approaches, the Tabu Search and Genetic Algorithm, were developed to solve a flexible job shop scheduling problem under a make-to-order production strategy. Each approach was validated using the case study, and the model's applicability were testes trough five instances. The results have shown that Tabu Search has a better efficacy and the Genetic Algorithm shows better efficiency.