Particle Swarm Optimization for Scheduling Batch Processing Machines in Permutation Flowshops

摘要

Particle Swarm Optimization (PSO) algorithm is a population-based meta-heuristic motivated by social behavior of organisms. PSO has been successfully applied to schedule discrete-processing machines in a flowshop. In this paper, we discuss the implementation of a PSO algorithm for scheduling batch processing machines in a permutation flowshop with the objective of minimizing the makespan. The results from PSO are compared with several heuristics. The computational results show that the proposed PSO algorithm performs better for the makespan objective.