A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for global optimization problems

• Published in: Applied soft computing Vol. 77; pp. 567 - 583
• Main Authors: Truong, Khoa H., Nallagownden, Perumal, Baharudin, Zuhairi, Vo, Dieu N.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-04-2019
• Subjects: Chaotic local search; Distributed generation; Global optimization problems; Meta-heuristic quasi-opposition-based learning; Symbiotic organisms search; Global optimization problems; Distributed generation; Chaotic local search; Meta-heuristic quasi-opposition-based learning; Symbiotic organisms search
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2019.01.043

This study proposes an improved version of the Symbiotic Organisms Search (SOS) algorithm called Quasi-Oppositional Chaotic Symbiotic Organisms Search (QOCSOS). This improved algorithm integrated Quasi-Opposition-Based Learning (QOBL) and Chaotic Local Search (CLS) strategies with SOS for a better quality solution and faster convergence. To demonstrate and validate the new algorithm’s effectiveness, the authors tested QOCSOS with twenty-six mathematical benchmark functions of different types and dimensions. In addition, QOCSOS optimized placements for distributed generation (DG) units in radial distribution networks and solved five structural design optimization problems, as practical optimization problems challenges. Comparative results showed that QOCSOS provided more accurate solutions than SOS and other methods, suggesting viability in dealing with global optimization problems.
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•An improved algorithm called Quasi-Oppositional Chaotic Symbiotic Organisms Search (QOCSOS) is presented for solving global optimization problems.•QOCSOS is tested on twenty-six mathematical benchmark functions.•QOCSOS is applied to solve an optimal DG placement problem in radial distribution networks.•QOCSOS is applied to solve five engineering design problems.•For all application, QOCSOS achieved better solution quality than other methods.