计算机应用研究2025，Vol.42Issue(6)：1698-1705,8.DOI:10.19734/j.issn.1001-3695.2024.10.0443
基于改进多目标鲸鱼优化算法的云制造鲁棒服务组合方法
Robust service composition method for cloud manufacturing based on improved multi-objective whale optimization algorithm
摘要
Abstract
Existing cloud manufacturing service composition methods are typically developed under the assumption of no anomalies in manufacturing services,which renders current models and methods inefficient or even prone to failure when ser-vice anomalies occur.To address this issue,this paper proposed a robust service composition method for cloud manufacturing based on an improved multi-objective whale optimization algorithm.Firstly,the method effectively avoided issues such as inef-ficiency or task failure caused by anomalies in preferred services by assigning a preferred service and an alternative service to each subtask.Next,the method used task latency time as a robustness indicator for cloud manufacturing services and construc-ted a multi-objective cloud manufacturing service composition model that considered both robustness and quality of service re-quirements.To solve this model,the method designed an improved multi-objective whale optimization algorithm based on a hy-brid strategy.Finally,analysis of different arithmetic cases shows that the proposed method outperforms other good methods of convergence and diversity.关键词
服务组合/云制造/多目标优化/鲁棒性/鲸鱼优化算法Key words
service composition/cloud manufacturing/multi-objective optimization/robustness/whale optimization algo-rithm分类
信息技术与安全科学引用本文复制引用
尹祖恒,徐洪珍..基于改进多目标鲸鱼优化算法的云制造鲁棒服务组合方法[J].计算机应用研究,2025,42(6):1698-1705,8.基金项目
国家自然科学基金资助项目(62466001) （62466001）
江西省抚州市领军人才计划项目(2021ED008) （2021ED008）
江西省网络空间安全智能感知重点实验室开放项目(JKLCIP202202) （JKLCIP202202）
江西省抚州市重点揭榜挂帅项目(2023JBB026) （2023JBB026）
