Cooperative Model of Evolutionary Algorithms and Real-World Problems

• Published in: Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing Vol. 1092; pp. 1 - 12
• Main Author: Bujok, Petr
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2020; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: CMA-ES; CoBiDE; Cooperation; Evolutionary algorithm; IDEbd; jSO; Real-world problems
• ISBN: 3030378373; 9783030378370
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-37838-7_1

A cooperative model of efficient evolutionary algorithms is proposed and studied when solving 22 real-world problems of the CEC 2011 benchmark suite. Four adaptive algorithms are chosen for this model, namely the Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) and three variants of adaptive Differential Evolution (CoBiDE, jSO, and IDEbd). Five different combinations of cooperating algorithms are tested to obtain the best results. Although the two algorithms use constant population size, the proposed model employs an efficient linear population-size reduction mechanism. The best performing Cooperative Model of Evolutionary Algorithms (CMEAL) employs two EAs, and it outperforms the original algorithms in 10 out of 22 real-world problems.