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A hybrid nested partitions algorithm for scheduling flexible resource in flow shop problem |
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| Authors: | Wei Wu Junhu Wei Xiaohong Guan Leyuan Shi |
| Affiliation: | 1. SKLMSE Laboratory, MOE KLINNS Laboratory, Systems Engineering Institute , Xi'an Jiaotong University , Xi'an , China mr.allawn@gmail.com;3. SKLMSE Laboratory, MOE KLINNS Laboratory, Systems Engineering Institute , Xi'an Jiaotong University , Xi'an , China;4. SKLMSE Laboratory, MOE KLINNS Laboratory, Systems Engineering Institute , Xi'an Jiaotong University , Xi'an , China;5. Center for Intelligent and Networked Systems , Tsinghua University , Beijing , China;6. Center for Intelligent and Networked Systems , Tsinghua University , Beijing , China;7. Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , Wisconsin , USA |
| Abstract: | Production scheduling with flexible resources is critical and challenging in many modern manufacturing firms. This paper applies the nested partitions (NP) framework to solve the flexible resource flow shop scheduling (FRFS) problem using an efficient hybrid NP algorithm. By considering the domain knowledge, the ordinal optimisation principle and the NEH heuristics are integrated into the partitioning scheme to search the feasible region. An efficient resource-allocation procedure is built into the sampling scheme for the FRFS problem. A large number of benchmark examples with flexible resources are tested. The test results show that the hybrid NP algorithm is more efficient than either generic NP or heuristics alone. The algorithm developed in this study is capable of selecting the most promising region for a manufacturing system with a high degree of accuracy. The algorithm is efficient and scalable for large-scale problems. |
| Keywords: | flow shop scheduling manufacturing systems manufacturing systems engineering resource planning scheduling optimisation |