Differential Evolution Combined with Constraint Consensus for Constrained Optimization

被引：0

作者：

Hamza, Noha M. ^{[1
]}

Elsayed, Saber M. ^{[1
]}

Essam, Daryl L. ^{[1
]}

Sarker, Ruhul A. ^{[1
]}

机构：

[1] Univ New S Wales, Australian Def Force Acad, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia

来源：

2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年

关键词：

Constrained optimization; constraint consensus; differential evolution;

D O I：

暂无

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：

Solving a Constrained Optimization Problem (COP) is much more challenging than its unconstrained counterpart. In solving COPs, the feasibility of a solution is a prime condition that requires the conversion of one or more infeasible individuals to feasible individuals. In this paper, to encourage the effective movement of infeasible individuals towards a feasible region, we introduce a Constraint Consensus (CC) method within the Differential Evolution (DE) algorithm for solving COPs. The algorithm has been tested by solving 13 well-known benchmark problems. The experimental results show that the solutions are competitive, if not better, as compared to the state of the art algorithms.

引用

页码：865 / 872

页数：8

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