Paper Info
Title
Parasite Diversity in Symbiogenetic Multiset Genetic Algorithm: Optimization of Large Binary Problems
Abstract
Symbiogenetic MuGA (SMuGA) is a co-evolutionary model exploiting the concept of symbiosis over the Multiset Genetic Algorithm (MuGA). It evolves two species: hosts that represent a solution to the problem, and parasites that represent part-solutions. SMuGA has been proved valuable in the optimization of a variety of deceptive functions. However its performance decreased in large scale difficult problems. This paper presents a new version of SMuGA with improvements centered on the evolution process of the parasites. The most significant advance is provided by using a diversity measure to modulate the evolution of parasites. The algorithm is tested with very good results in deceptive functions with up to 1024 bits. The paper is concluded with an analysis of the advantages and limitations of the approach, and with perspectives for future developments.
Year
DOI
Venue
2015
10.1145/2739480.2754780
Genetic and Evolutionary Computation Conference
Keywords
Field
DocType
Multiset, Symbiosis, Genetic diversity, Genetic operators, Deceptive problems
Diversity measure,Genetic diversity,Multiset,Computer science,Genetic algorithm optimization,Artificial intelligence,Genetic algorithm,Binary number
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
António Manuel Rodrigues Manso151.11
Luis M. Correia228455.53