A Niching Multi-objective Harmony Search Algorithm for Multimodal Multi-objective Problems

被引：0

作者：

Qu, B. Y. ^{[1
]}

Li, G. S. ^{[1
]}

Guo, Q. Q. ^{[1
]}

Yan, L. ^{[1
]}

Chai, X. Z. ^{[1
]}

Guo, Z. Q. ^{[2
]}

机构：

[1] Zhongyuan Univ Technol, Sch Elect & Informat Engn, Zhengzhou 450007, Henan, Peoples R China

[2] Henan Xuchang Senior High Sch, Xuchang 461000, Peoples R China

来源：

2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2019年

基金：

中国国家自然科学基金;

关键词：

Evolutionary algorithm; multimodal multi-objective problems; harmony search algorithm; niching technique; OPTIMIZATION ALGORITHM; GENETIC ALGORITHM; CONTROLLER; MODEL; EMOA;

D O I：

10.1109/cec.2019.8790286

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A modified multi-objective harmony search algorithm called Niching Multi-objective Harmony Search Algorithm (NMOHSA) is proposed to solve multimodal multi-objective optimization problems. It adopts the neighborhood information to build dynamic harmony memory for maintaining the population diversity. A new memory consideration rule is also applied to prevent the algorithm be trapped into local optimal solution. Moreover, two key parameters, harmony memory consideration rate (HMCR) and pitch adjustment rate (PAR), are dynamically adjusted. Empirical results show that the proposed algorithm performs much better than the other existing multimodal multi-objective algorithms in terms of the solution quality.

引用

页码：1267 / 1274

页数：8

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