An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem

Hybrid flow shops (HFS) are common manufacturing environments in many industries, such as the glass, steel, paper and textile industries. In this paper, we present a particle swarm optimization (PSO) algorithm for the HFS scheduling problem with minimum makespan objective. The main contribution of this paper is to develop a new approach hybridizing PSO with bottleneck heuristic to fully exploit the bottleneck stage, and with simulated annealing to help escape from local optima. The proposed PSO algorithm is tested on the benchmark problems provided by Carlier and Néron. Experimental results show that the proposed algorithm outperforms all the compared algorithms in solving the HFS problem.

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► This paper presents a particle swarm optimization (PSO) for hybrid flow shop (HFS).
► A new approach hybridizing PSO with bottleneck heuristic and SA is developed.
► The proposed algorithm outperforms all the compared algorithms in solving HFS.