A new algorithm inspired in the behavior of the social-spider for constrained optimization

作者：

Highlights：

• In this paper, a novel swarm algorithm called the Social Spider Optimization (SSO-C) is proposed for solving constrained optimization tasks.

• In the proposed method, individuals emulate a group of spiders which interact to each other based on the biological laws of the cooperative colony.

• For constraint handling, the approach incorporates the combination of two different paradigms: a penalty function and a feasibility criterion.

• Comparisons based on several well-studied benchmarks functions demonstrate the effectiveness, efficiency and stability of the proposed method.

摘要

•In this paper, a novel swarm algorithm called the Social Spider Optimization (SSO-C) is proposed for solving constrained optimization tasks.•In the proposed method, individuals emulate a group of spiders which interact to each other based on the biological laws of the cooperative colony.•For constraint handling, the approach incorporates the combination of two different paradigms: a penalty function and a feasibility criterion.•Comparisons based on several well-studied benchmarks functions demonstrate the effectiveness, efficiency and stability of the proposed method.

论文关键词：Swarm algorithms,Constrained optimization,Bio-inspired algorithms

论文评审过程：Available online 27 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.067