October 2017
Intermediate to advanced
304 pages
8h 3m
English
book
Meta-heuristic and Evolutionary Algorithms for Engineering Optimization
by Omid Bozorg-Haddad, Mohammad Solgi, Hugo A. Loáiciga
Content preview from Meta-heuristic and Evolutionary Algorithms for Engineering Optimization
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21 Symbiotic Organisms Search
Summary
This chapter describes the symbiotic organisms search (SOS) algorithm, a recently developed meta‐heuristic algorithm. Unlike most of meta‐heuristic algorithms, the SOS does not require specification of algorithmic parameters. First, the basic concepts of the SOS algorithm are mapped to the symbiotic relations among organisms. The steps of the SOS algorithm are defined in detail and a pseudocode of the SOS is presented.
21.1 Introduction
Cheng and Prayogo (2014) introduced the symbiotic organisms search (SOS) algorithm. The SOS is a nature‐inspired optimization algorithm that simulates three different symbiosis interactions within a paired organism relationship through an ecosystem. Evolutionary algorithms (EAs) are targets of criticism because of the need for specifying algorithmic parameters. The SOS algorithm requires only the specification of the “maximum number of evaluations” and the “population size.” Evi et al. (2015) implemented the SOS for solving capacitated vehicle routing problem (CVRP). Rajathy et al. (2015) demonstrated the superiority of the SOS for solving economic load dispatch problem.
21.2 Mapping Symbiotic Relations to the Symbiotic Organisms Search (SOS)
Symbiosis is a close physical relation between two interacting organisms. There are three categories of symbiotic relationships including mutualism, commensalism, and parasitism. Mutualism is a relation that is beneficial to both organisms involved. In many ...
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