Particle Swarm Optimization for Scheduling Batch ProcessingMachines in Permutation Flowshops

摘要

Particle Swarm Optimization (PSO) algorithm is a population-based meta-heuristic motivated by social behavior oforganisms. 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 permutationflowshop with the objective of minimizing the makespan. The results from PSO are compared with severalheuristics. The computational results show that the proposed PSO algorithm performs better for the makespanobjective.