Parallel-machine scheduling problems with sequence-dependent setup times using an ACO,SA and VNS hybrid algorithm |
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| Authors: | J Behnamian M Zandieh SMT Fatemi Ghomi |
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| Affiliation: | 1. Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, Tehran, Iran;2. Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran;1. Department of Management Science & Engineering, School of Economics & Management, Tongji University, Shanghai 200029, PR China;2. Department of Industrial Engineering, School of Mechanical Engineering, Tongji University, Shanghai 200029, PR China;1. Department of Mechanical Engineering, Jadavpur University, Kolkata 700032, India;2. College of Business, University of Alabama in Huntsville, Huntsville, AL, USA;1. Integration and Collaboration Laboratory, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, P.O. Box 24-60, Hsinchu 300, Taiwan, ROC;2. Department of Mathematics, National Kaohsiung Normal University, Kaohsiung 824, Taiwan, ROC;3. Department of Statistics, Feng Chia University, Taichung, Taiwan;1. School of Management, Hefei University of Technology, Hefei 230009, PR China;2. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009, PR China;3. Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA |
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| Abstract: | This paper proposes a hybrid metaheuristic for the minimization of makespan in scheduling problems with parallel machines and sequence-dependent setup times. The solution approach is robust, fast, and simply structured, and comprises three components: an initial population generation method based on an ant colony optimization (ACO), a simulated annealing (SA) for solution evolution, and a variable neighborhood search (VNS) which involves three local search procedures to improve the population. The hybridization of an ACO, SA with VNS, combining the advantages of these three individual components, is the key innovative aspect of the approach. Two algorithms of a hybrid VNS-based algorithm, SA/VNS and ACO/VNS, and the VNS algorithm presented previously are used to compare with the proposed hybrid algorithm to highlight its advantages in terms of generality and quality for large instances. |
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