Memetic algorithms and memetic computing optimization: A literature review

• Published in: Swarm and evolutionary computation Vol. 2; pp. 1 - 14
• Main Authors: Neri, Ferrante, Cotta, Carlos
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2012
• Subjects: Computational intelligence optimization; Evolutionary algorithms; Memetic algorithms; Memetic computing; Memetic computing; Memetic algorithms; Evolutionary algorithms; Computational intelligence optimization
• ISSN: 2210-6502
• DOI: 10.1016/j.swevo.2011.11.003

Memetic computing is a subject in computer science which considers complex structures such as the combination of simple agents and memes, whose evolutionary interactions lead to intelligent complexes capable of problem-solving. The founding cornerstone of this subject has been the concept of memetic algorithms, that is a class of optimization algorithms whose structure is characterized by an evolutionary framework and a list of local search components. This article presents a broad literature review on this subject focused on optimization problems. Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties, are addressed by indicating the memetic “recipes” proposed in the literature. In addition, this article focuses on implementation aspects and especially the coordination of memes which is the most important and characterizing aspect of a memetic structure. Finally, some considerations about future trends in the subject are given.