Simulation optimization using particle swarm optimization algorithm with application to assembly line design

Assembly line design is an important part of production system. Some processes need to undergo changes in order to increase in efficiency. Computer simulation has been applied on process design for many decades. Traditionally, simulation had to run all possible alternatives of assembly line and was not considered as an optimization technique. Thus, this study employs particle swarm optimization (PSO) algorithm which is with mutation based on similarity for simulation optimization in order to optimize the managerial parameters in production system. Through experimentation designs and statistics tests, the simulation results show that the proposed method is better than other algorithms, like genetic algorithm and conventional PSO algorithm for solving assembly line design problem.