Hybrid flexible flowshop problems: Models and solution methods

This paper considers the problem of hybrid flowshop scheduling. First, we review the shortcoming of the available model in the literature. Then, four different mathematical models are developed in form of mixed integer linear programming models. A complete experiment is conducted to compare the models for performance based on the size and computational complexities. Besides the models, the paper proposes a novel hybrid particle swarm optimization algorithm equipped with an acceptance criterion and a local search heuristic. The features provide a fine balance of diversification and intensification capabilities for the algorithm. Using Taguchi method, the algorithm is fine tuned. Then, two numerical experiments are performed to evaluate the performance of the proposed algorithm with three particle swarm optimization algorithms available in the scheduling literature and one well-known iterated local search algorithm in the hybrid flowshop literature. All the results show the high performance of the proposed algorithm.