Hybrid sliding level Taguchi-based particle swarm optimization for flowshop scheduling problems |
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| Affiliation: | 1. Department of Computer Science, National Pingtung University of Education, 4-18 Min-Sheng Road, Pingtung 900, Taiwan, ROC;2. Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, 1 University Road, Yenchao, Kaohsiung 824, Taiwan, ROC;3. Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, Kaohsiung 807, Taiwan, ROC;4. Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, 100 Shi-Chuan 1st Road, Kaohsiung 807, Taiwan, ROC;1. State Key Laboratory for Manufacturing Systems Engineering, and Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, PR China;2. School of Sciences, Guizhou Institute of Technology, Guiyang 550003, PR China;1. School of Telecommunication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an, PR China;2. School of Computer Science, Shaanxi Normal University, Xi’an, PR China;1. Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Ave., Cleveland, OH 44106, USA;2. Department of Management Science and Information Systems, Rutgers Business School Newark and New Brunswick, 1 Washington Park, Newark, NJ 07102, USA;3. Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., 15875-4413 Tehran, Iran;4. Department of Industrial Engineering, University of Science & Culture, Ashrafie Esfahani Ave., Tehran, Iran |
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| Abstract: | A hybrid sliding level Taguchi-based particle swarm optimization (HSLTPSO) algorithm is proposed for solving multi-objective flowshop scheduling problems (FSPs). The proposed HSLTPSO integrates particle swarm optimization, sliding level Taguchi-based crossover, and elitist preservation strategy. The novel contribution of the proposed HSLTPSO is the use of a PSO to explore the optimal feasible region in macro-space, the use of a systematic reasoning mechanism of the sliding level Taguchi-based crossover to exploit the better solution in micro-space, and the use of the elitist preservation strategy to retain the best particles of multi-objective population for next iteration. The sliding level Taguchi-based crossover is embedded in the PSO to find the best solutions and consequently enhance the PSO. Using the systematic reasoning way of the Taguchi-based crossover with considering the influence of tuning factors α, β and γ is presented in this study to solve the conflicting problem of non-feasible solutions and to find the better particles. As a result, it exhibits a significant improvement in Pareto best solutions of the FSP. By combining the advantages of exploration and exploitation, from the computational experiments of the six test problems, the HSLTPSO provides better results compared to the existing methods reported in the literature when solving multi-objective FSPs. Therefore, the HSLTPSO is an effective approach in solving multi-objective FSPs. |
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| Keywords: | Flowshop scheduling problem Sliding level Taguchi-based particle swarm optimization Taguchi-based crossover |
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