Hybrid Evolutionary Algorithm for Multi-Objective Job Shop Scheduling
In this paper, a hybrid quantum-inspired evolutionary algorithm (HQEA) for multi-objective.ISSP is proposed. In the HQEA, a quantum bit is employed to represent processing priority of two operations executed on the same machine. Updating operator of quantum gate is used to speed up individuals converge toward the current best solution. Conventional crossover is performed as well. However, an individual produced by updating operator and crossover operator may represent no feasible schedule. To repair illegal solution, harmonization algorithm is employed. At last, local search operator is designed to exploit the space around the current best solution. Experiments are conducted on benchmark test problems, the results show that the proposed approach can search for the near-optimal and non dominated solutions by optimizing the makes pan and mean flow time. The results of comparisons demonstrates that the proposed approach outperform another well established multi-objective evolutionary algorithm based JSSP approach.
Multi-objective job shop scheduling Quantum-inspired evolutionary algorithm Local search
Chaoyong Qin Jiajun Zhu Jianguo Zheng
School of Math and Information Science,Guangxi University No.100 Daxue Road,Nanning,P.R.China School of Business and Management,Donghua University No.1882 Yanan Road,Shanghai,P.R.China, School of Business and Management,Donghua University No.1882 Yanan Road,Shanghai,P.R.China
国际会议
上海
英文
1071-1076
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）