A Monte Carlo simulation based chaotic differential evolution algorithm for scheduling a stochastic parallel processor system
作者：
Highlights：
• A simulation-based evolutionary optimization is proposed for a parallel processor system.
• A lower level Monte Carlo and an upper level differential evolution are suggested.
• Simulation is used to assess quality of candidate solutions and optimizer is utilized to guide the search at upper level.
• Chaos theory is employed to enhance quality of results via preventing premature convergence and locality.
摘要
•A simulation-based evolutionary optimization is proposed for a parallel processor system.•A lower level Monte Carlo and an upper level differential evolution are suggested.•Simulation is used to assess quality of candidate solutions and optimizer is utilized to guide the search at upper level.•Chaos theory is employed to enhance quality of results via preventing premature convergence and locality.
论文关键词：Chaos theory,Chaotic maps,Simulation-based optimization,Differential evolution,Parallel processor system scheduling
论文评审过程：Available online 18 May 2015, Version of Record 3 June 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.05.015
