Swarm‐Based Optimization Algorithms
Konstantinos E. Parsopoulos, Marco A. Montes de · Wiley Encyclopedia of Electrical and Electronics Engineering · 2017
Abstract Swarm‐based optimization algorithms have prevailed in the field of metaheuristics for the past decades. With their application field spanning from combinatorial problems to continuous and mixed integer problems, swarm‐based algorithms are currently part of the state‐of‐the‐art in search and optimization. The main search mechanisms of swarm‐based algorithms are based on models of swarms found in the natural world. These models include swarms ranging from the macroscopic level (living organisms) to the microscopic level (elementary particles). It is surprising that similar dynamics and motion patterns are discovered in such diverse systems. These properties are responsible for the collective intelligent behavior exhibited by swarms, even when their constituent entities lack intelligent behavior properties. The present article aims at discussing the main properties that govern the swarming behavior and reviewing some of the most popular swarm‐based optimization algorithms.