A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation |
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| Affiliation: | 1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;2. College of Computer Science, Liaocheng University, Liaocheng 252059, China;3. Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing 100084, China;1. Mathematical Sciences, Brunel University, Uxbridge UB8 3PH, UK;2. Business School, Imperial College, London SW7 2AZ, UK;3. JB Consultants, Morden SM4 4HS, UK;1. Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, North Cyprus via Mersin 10, Turkey;2. Department of Industrial Engineering, Middle East Technical University, Ankara 06800, Turkey;1. Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu 626001, India;2. Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu 626005, India;3. School of Science and Technology, Middlesex University, London NW4 4BT, UK;1. School of Automation, Wuhan University of Technology, Wuhan 430070, China;2. State Key Lab of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;3. Faculty of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China |
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| Abstract: | The hybrid flowshop scheduling (HFS) problem with the objective of minimising the makespan has important applications in a variety of industrial systems. This paper presents an effective discrete artificial bee colony (DABC) algorithm that has a hybrid representation and a combination of forward decoding and backward decoding methods for solving the problem. Based on the dispatching rules, the well-known NEH heuristic, and the two decoding methods, we first provide a total of 24 heuristics. Next, an initial population is generated with a high level of quality and diversity based on the presented heuristics. A new control parameter is introduced to conduct the search of employed bees and onlooker bees with the intention of balancing the global exploration and local exploitation, and an enhanced strategy is proposed for the scout bee phase to prevent the algorithm from searching in poor regions of the solution space. A problem-specific local refinement procedure is developed to search for solution space that is unexplored by the honey bees. Afterward, the parameters and operators of the proposed DABC are calibrated by means of a design of experiments approach. Finally, a comparative evaluation is conducted, with the best performing algorithms presented for the HFS problem under consideration, and with adaptations of some state-of-the-art metaheuristics that were originally designed for other HFS problems. The results show that the proposed DABC performs much better than the other algorithms in solving the HFS problem with the makespan criterion. |
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| Keywords: | Hybrid flowshop Makespan Heuristics Metaheuristics Artificial bee colony |
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