Ant colony optimization for multi-objective flow shop scheduling problem |
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| Authors: | Betul Yagmahan Mehmet Mutlu Yenisey |
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| Affiliation: | 1. Department of Industrial Engineering, Faculty of Engineering and Architecture, Uludag University, Gorukle Campus, Bursa 16059, Turkey;2. Department of Industrial Engineering, Istanbul Technical University, Macka 34367, Istanbul, Turkey;1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;2. Brunel Business School, Brunel University, Uxbridge, Middlesex, UK;1. Département de mathématiques et génie industriel, Polytechnique Montréal, Montréal, Canada;2. Dipartimento di Meccanica, Politecnico di Milano, Milano, Italy;1. Department of Automation, Tsinghua University, Beijing, 100084, China;2. School of Computer, Guangdong University of Petrochemical Technology, Maoming, 525000, China;1. Department of Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran;2. Department of Industrial Engineering, Payame Noor University, Tehran, Iran;3. Department of Industrial Engineering, University of Tehran, Tehran, Iran |
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| Abstract: | Flow shop scheduling problem consists of scheduling given jobs with same order at all machines. The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, multi-objective approach for scheduling to reduce the total scheduling cost is important. Hence, in this study, we consider the flow shop scheduling problem with multi-objectives of makespan, total flow time and total machine idle time. Ant colony optimization (ACO) algorithm is proposed to solve this problem which is known as NP-hard type. The proposed algorithm is compared with solution performance obtained by the existing multi-objective heuristics. As a result, computational results show that proposed algorithm is more effective and better than other methods compared. |
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