A combinatorial particle swarm optimisation for solving permutation flowshop problems

The m-machine permutation flowshop problem PFSP with the objectives of minimizing the makespan and the total flowtime is a common scheduling problem, which is known to be NP-complete in the strong sense, when m>=3. This work proposes a new algorithm for solving the permutation FSP, namely combinatorial Particle Swarm Optimization. Furthermore, we incorporate in this heuristic an improvement procedure based on the simulated annealing approach. The proposed algorithm was applied to well-known benchmark problems and compared with several competing metaheuristics.