A simulation-based genetic algorithm approach for remanufacturing process planning and scheduling |
| |
| Affiliation: | 1. School of Management, Xiamen University of Technology, Xiamen 361024, PR China;2. Department of Mechanical Engineering, National University of Singapore, Singapore 117576, Singapore;1. Mechanical Engineering Department, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec H3C 1K3, Canada;2. Automated Production Engineering Department, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec H3C 1K3, Canada;1. Department of Mechanical, Energy, Management, and Transportation Engineering (DIME), University of Genova, Via Montallegro 1, 16145 Genova, Italy;2. Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genova, Via Opera Pia 13, 16145 Genova, Italy;1. School of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, PR China;2. School of Economics and Management, Fuzhou University, Fuzhou, Fujian 350116, PR China;3. School of Management, Hefei University of Technology, Hefei, Anhui 230009, PR China;1. Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Shaanxi, 710072, PR China;2. Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;3. Department of Management and Engineering, Linköping University, SE-581 83, Linköping, Sweden;4. Department of Production, University of Vaasa, Vaasa, Finland;5. School of Mechanical Engineering, Guangdong University of Technology, Guangzhou, PR China;6. Institute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN, USA |
| |
| Abstract: | Remanufacturing has attracted growing attention in recent years because of its energy-saving and emission-reduction potential. Process planning and scheduling play important roles in the organization of remanufacturing activities and directly affect the overall performance of a remanufacturing system. However, the existing research on remanufacturing process planning and scheduling is very limited due to the difficulty and complexity brought about by various uncertainties in remanufacturing processes. We address the problem by adopting a simulation-based optimization framework. In the proposed genetic algorithm, a solution represents the selected process routes for the jobs to be remanufactured, and the quality of a solution is evaluated through Monte Carlo simulation, in which a production schedule is generated following the specified process routes. The studied problem includes two objective functions to be optimized simultaneously (one concerned with process planning and the other concerned with scheduling), and therefore, Pareto-based optimization principles are applied. The proposed solution approach is comprehensively tested and is shown to outperform a standard multi-objective optimization algorithm. |
| |
| Keywords: | Process planning and scheduling Remanufacturing Genetic algorithm Multi-objective optimization |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
