摘要
为解决云制造环境下复杂制造任务的服务组合问题,促进云制造模式的良性发展,构建综合考虑服务需求方、云制造平台和服务提供方三方利益的多目标服务组合优化模型。基于反向学习机制和多目标种群自适应进化机制改进NSGA-Ⅲ算法,并将该算法应用于多目标服务组合优化模型求解。通过比较NSGA-Ⅲ算法与改进NSGA-Ⅲ算法的各个方向适应度的均值和方差,验证了后者在求解多目标服务组合优化问题上的有效性。
To solve the service composition problem of complex manufacturing tasks in cloud manufacturing environment and promote the healthy development of cloud manufacturing mode,a multi-objective service composition optimization model is constructed that comprehen⁃sively considers the interests of service demanders,cloud manufacturing platforms,and service providers.Based on the reverse learning mech⁃anism and multi-objective population adaptive evolution mechanism,the NSGA-III algorithm is improved and applied to solve the multi-ob⁃jective service composition optimization model.By comparing the mean and variance of fitness in various directions of the NSGA-III algo⁃rithm with the improved NSGA-III algorithm,the effectiveness of the latter in solving multi-objective service composition optimization prob⁃lems was verified.
作者
王平
周鑫
WANG Ping;ZHOU Xin(School of Economics and Management,Jiangsu University of Science and Technology;Research Center of Service Manufactur-ing Mode and Informationization,Jiangsu University of Science and Technology,Zhenjiang 212003,China)
出处
《软件导刊》
2024年第3期71-79,共9页
Software Guide
基金
国家社会科学基金项目(22BJY021)。
关键词
云制造
多目标优化
反向学习
自适应进化
NSGA-Ⅲ
cloud manufacturing
multi objective optimization
reverse learning
adaptive evolution
NSGA-Ⅲ
