Solving a Multi-objective Production Scheduling by Genetic Algorithms

Production scheduling in plants, due to their hybrid nature, can become very complex. Manufacturers developed various manufacturing operations to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. This paper deals with a production scheduling problem in a flexible (or hybrid) job-shop with particular constraints: batch production; existence of two steps: production of several sub-products followed by the assembly of the final product; possible overlaps for the processing periods of two successive operations of a same job. Different objectives should be considered simultaneously, among the makespan, the mean completion time, the maximal tardiness, the mean tardiness. The main contribution of this paper is the presentation of a novel approach based on a genetic algorithm as a suitable tool for scheduling of hybrid systems. The major benefit of this approach is a significant reduction in complexity during problem formulation. The proposed method is explained through a mill case study.