Abstract
AbstractFor sampling various solutions from the entire Pareto front of the multiobjective resource division problem, a new Genetic Algorithm (GA) based on an evolutionary theory advocated by Kinji Imanishi is proposed. First, two types of distance between two individuals, namely, structural and functional distances, are introduced and used to define four types of relation between them, namely, homogeneous, heterogeneous, homologous, and analogous species. Then, for keeping a variety of species within a population as far as possible, a new generation alternation model with variable population size is presented. In order to find Pareto‐optimal solutions effectively, a new genetic operation that combines conventional harmonic crossover with a local optimization algorithm is also proposed. Finally, the advantage of the Imanishism‐based GA is demonstrated through computational experiments conducted on two‐ and three‐objective problem instances. © 2002 Scripta Technica, Electr Eng Jpn, 139(2): 23–35, 2002; DOI 10.1002/eej.10010
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
