基于改进型哈里斯鹰算法的云制造服务组合优化方法研究
Research on Cloud Manufacturing Service Composition Method Based on Improved Harris Hawks Optimization Algorithm
张舒淇 1唐敦兵 1张毅 1周世辉 1王威奇1
作者信息
- 1. 南京航空航天大学机电学院,江苏南京 210016
- 折叠
摘要
云制造环境下,云平台以制造服务组合的形式为个性化需求提供按需服务,可显著提升订单响应速度与提高资源利用率.采用哈里斯鹰算法构建制造服务组合,针对制造服务间物流转运问题,建立独特的编码与解码机制.为解决该算法存在早熟收敛问题,引入 Logistic 一维混沌系统,设计非线性逃逸能量更新机制和3种邻域搜索策略.通过实验验证了改进后的哈里斯鹰算法在解决云制造服务组合优化问题时具有显著优越性.
Abstract
In cloud manufacturing environment,the cloud platform provides on-demand services for personalized needs in the form of manufacturing service composition,which can significantly improve order response speed and resource utilization.This paper uses Harris Hawks optimization algorithm to construct manufacturing service composition,and establishes a unique coding and decoding mechanism for the logistics transfer between manufacturing services.In order to solve the premature convergence problem of the algorithm,the Logistic one-dimensional chaotic system is introduced,the nonlinear escape energy updating mechanism and three types of neighborhood search strategies are designed.Experiments verify the significant advantages of the improved Harris Hawk algorithm in solving the cloud manufacturing service portfolio optimization problem.
关键词
云制造/服务组合/哈里斯鹰算法/任务调度Key words
cloud manufacturing/service composition/Harris Hawks optimization algorithm/task scheduling引用本文复制引用
基金项目
国家重点研发计划项目(2020YFB1710500)
江苏省重点研发计划项目(BE2021091)
成飞-南航"智汇蓝天"校企协同育人项目(2022QYGCSJ38)
出版年
2024
国家科技期刊平台
NSTL
万方数据