Particle Swarm Optimization Algorithm for Makespan and Maximum Lateness Minimization in Permutation Flowshop Sequencing Problem

In this paper, a particle swarm optimization algorithm (PSO) is presented to solve the permutaion flowshop sequencing problem (PFSP) with the objectives of minimizing makespan and maximum lateness of jobs, respectively. Simple but very efficient local search based on variable neighborhood search (VNS) is embedded in the particle swarm optimization algorithm to solve the well known benchmark suites in the literature. The proposed PSO algorithm is applied to both 40 benchmark problems for makespan criterion and 160 problem instances for maximum lateness criterion provided by Demirkol et al. (European Journal of Operational Research, 109 (1998) 137-141). For both makespan and maximum lateness criteria, solution quality is evaluated according to the upper bounds provided by Demirkol. For makespan criterion, all of the upper bounds reported by Demirkol are improved while for maximum lateness criterion, a total of 155 out of 160 upper bounds is improved by the proposed VNS version of the PSO algorithm.