A Genetic Algorithm for Scheduling a Semi-Continuous Process Industry: A Case Study

In today's competitive industry, scheduling plays a significant role in improving the efficiency of manufacturing systems. Hence, many scholars and practitioners have been researching to enhance the quality of scheduling methods. In this research, the focus is on solving a real-world scheduling problem in a food industry which was previously dealt with a very time-consuming manual method without high-quality solutions. The problem is to find the best schedule for producing multiple products on multiple machines in a semi-continuous manufacturing system. Having a continuous section in the system makes scheduling too complicated and very different from typical scheduling problems found in literature. In this paper, metaheuristics based on genetic algorithm is proposed to solve the problem. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.