Application of metaheuristics in solving two-stage assembly scheduling problem

Abstract

The paper reports for the first time the solution of the two-stage assembly scheduling problem (TSASP) using the Hybrid Genetic Bees Algorithm (GBA). The aim of the research is to apply Genetic Bees Algorithm (GBA) to solve the two-stage assembly scheduling problem (TSASP) to minimize both the makespan and mean completion time where setup times are treated as separate from processing times. The hybrid of Genetic Algorithm (GA) and Bees Algorithm (BA) are combined to enhance both the exploration and exploitation. Three methods Particle Swam Optimization (PSO), Genetic Algorithm (GA) and Hybrid Genetic Bees Algorithm (GBA) are compared. Results showed that GBA are competitive and are better than PSO and GA in many instances, thus proving that GBA a realistic and efficient solution to the two-stage assembly scheduling problem.