A Multi-Objective Hybrid Differential Optimization Algorithm for Flow-Shop Scheduling Problem
作者: Pei, J. Y.Shan, P.
刊名: International Journal of Simulation Modeling, 2019, Vol.18 (3), pp.500-509
来源数据库: DAAAM International Vienna
DOI: 10.2507/IJSIMM18(3)CO11
关键词: Flow-Shop Scheduling Problem (FSP)Multi-Objective OptimizationHybrid Differential EvolutionGenetic Algorithms (GA)
原始语种摘要: This paper puts forward a multi-objective hybrid difference optimization algorithm to solve multi-objective flow-shop scheduling problem (FSP). The hybrid algorithm inherits the merits of differential evolution vector operation, and makes dynamic adjustments to the search direction based on historical data. However, the basic differential evolution algorithm is prone to the local optimum trap, due to the low population diversity in the later stage of evolution. To solve the problem, a hybrid sampling strategy was introduced obtain the distribution information of solution sets and to design the mutation operator of differential evolution, thus improving the convergence of the hybrid algorithm. Finally, our algorithm was applied to solve FSPs through simulation. The simulation results show...
全文获取路径: 国际维也纳多瑙河亚德里亚自动化与制造协会  (合作)

  • evolution 进化
  • objective 接物镜
  • differential 差动的
  • convergence 汇合
  • solve 
  • algorithm 算法
  • scheduling 
  • operator 话务员
  • obtain 获得
  • simulation 模拟