Using Non-dominated Sorting Particle Swarm Optimization Algorithm II for Bi-objective Flow Shop Scheduling Problems

A hybrid particulate swarm optimization (hybrid) combination of an algorithm the particle and a variable neighborhood search is proposed for multi-objective permutation flow shop scheduling problem (PFSP) with smallest cumulative completion time total time. Algorithm (HPSO) applied to maintain fair centralized decentralized search. The Nawaz-Enscore-Ham )NEH) heuristic in this used initialize populations order improve efficiency initial solution. method design based on ascending (ranked-order-value, ROV), applying continuous PSO PFSP, introducing external archive set storage Pareto solution, using strategy that combines strong dominance aggregation distance ensure distribution solution set. We adopted Sigma roulette method, distance, select global optimal was further suggested solve Taillard test equate results SPEA2 check algorithm’s efficacy.