A hybrid genetic algorithm for the flow-shop scheduling problem

Authors:
Lin-Yu Tseng;Ya-Tai Lin
Affiliations:
Department of Computer Science, National Chung Hsing University, Taichung, Taiwan;Department of Computer Science, National Chung Hsing University, Taichung, Taiwan
Venue:
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Year:
2006

Citing 5
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Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance

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A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion

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Genetic algorithms, path relinking, and the flowshop sequencing problem

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Genetic algorithm-based heuristics for an open shop scheduling problem with setup, processing, and removal times separated

Robotics and Computer-Integrated Manufacturing

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Abstract

The flow-shop scheduling problem with the makespan criterion is an important production scheduling problem. Although this problem has a simple formulation, it is NP-hard. Therefore many heuristic and metaheuristic methods had been proposed to solve this problem. In this paper, a hybrid genetic algorithm is presented for the flow-shop scheduling problem. In our method, a modified version of NEH with random re-start is used to generate the initial population. Also, a new orthogonal array crossover is devised as the crossover operator of the genetic algorithm. The tabu search is hybridized with the genetic algorithm and acts as the local search method. The proposed algorithm had been tested on two benchmarks. The results are compared with those of other methods that had also been tested on these benchmarks. The comparison shows that our method outperforms other methods on these benchmarks.