Social Algorithms

TL;DR

This paper reviews social algorithms, a class of swarm intelligence-based optimization methods that mimic social and biological behaviors of animals like ants, bees, and birds to solve complex problems.

Contribution

It provides a comprehensive review of social algorithms, highlighting their design principles and biological inspirations for optimization tasks.

Findings

Social algorithms effectively solve complex optimization problems.

They mimic social behaviors of animals for algorithm design.

The review discusses various social algorithms and their applications.

Abstract

This article concerns the review of a special class of swarm intelligence based algorithms for solving optimization problems and these algorithms can be referred to as social algorithms. Social algorithms use multiple agents and the social interactions to design rules for algorithms so as to mimic certain successful characteristics of the social/biological systems such as ants, bees, bats, birds and animals.