Abstract
The continues in real-world problems increasing complexity motivated computer scientists and researchers to search for more-efficient problem-solving strategies. Generally natural Inspired, Bio Inspired, Metaheuristics based on evolutionary computation and swarm intelligence algorithms have been frequently used for solving complex, real-world optimization problems because of their ability to adjust to variety of conditions. This paper present a swarm based algorithm that is based on the cooperative behaviors between social spider, it called Social Spider Optimization (SSO) algorithm. In SSO, search agents characterize a set of spiders which together move according to a biological behavior in colony. During the past years after SSO introduction, many modifications has improved the performance of the algorithm and has been applied in several fields. In this paper, the improvements, and applications of the SSO are reviewed.
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