Real-Time Order Acceptance and Scheduling Problems in a Flow Shop Environment Using Hybrid GA-PSO Algorithm

With the emergence of new Industry 4.0 technologies, real-time order acceptance and scheduling is a key problem in a make-to-order (MTO) production system where customers place orders in real-time and the decision maker has to make acceptance or rejection decisions based on the available resources at that point in time. This paper focuses on simultaneously accepting orders and scheduling decisions in real-time, as is required for the operation of an MTO flow shop production system, a topic that has received little attention in academia due to the complexity of the problem. This paper presents a hybrid genetic algorithm and particle swarm optimization algorithm (GA-PSO) to solve the considered problem. A detailed computational study based on realistic problem instances has been conducted. In this study, the hybrid GA- and PSO-based approach performed better than other state-of-the-art approaches reported in the literature.