Evolutionary Competitive Multitasking Optimization

被引：46
作者：
Li, Genghui [1 ,2 ]
Zhang, Qingfu [2 ,3 ]
Wang, Zhenkun [1 ,4 ]
机构：
[1] Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen 518055, Peoples R China
[2] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[3] City Univ Hong Kong, Shenzhen Res Inst, Shenzhen 518057, Peoples R China
[4] Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen 518055, Peoples R China
来源：
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION | 2022年 / 26卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Task analysis; Optimization; Multitasking; Resource management; Statistics; Sociology; Evolutionary computation; Competitive multitasking optimization problem (CMTOP); information transfer; online resources allocation; task selection; ALGORITHM;
D O I：
10.1109/TEVC.2022.3141819
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article introduces a special multitasking optimization problem (MTOP) called the competitive MTOP (CMTOP). Its distinctive characteristics are that all tasks' objectives are comparable, and its optimal solution is the best one among the optimal solutions of all the individual problems. This article proposes an evolutionary algorithm with an online resource allocation strategy and an adaptive information transfer mechanism to solve the CMTOP. The experimental results on benchmark and real-world problems show that our proposed algorithm is effective and efficient.
引用
收藏
页码：278 / 289
页数：12
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