title: A PSO-based hybrid metaheuristic for permutation flowshop scheduling problems.
abstract: This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.
authors.affiliation: School of Information Engineering, Shenyang University, Shenyang 110044, China ; School of Information Science and Technology, Tsinghua University, Beijing 100084, China.
authors.forename: Le
authors.initials: L
authors.lastname: Zhang
authors.affiliation: School of Information Engineering, Shenyang University, Shenyang 110044, China.
authors.forename: Jinnan
authors.initials: J
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical