An adaptive method of Hungarian mating schemes in genetic algorithms
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, C. | - |
dc.contributor.author | Kim, Y.-H. | - |
dc.contributor.author | Yoon, Y. | - |
dc.contributor.author | Moon, B.-R. | - |
dc.date.available | 2020-02-28T11:41:12Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/11042 | - |
dc.description.abstract | Mating scheme is one of the key operations in genetic algorithms. In this paper, we propose an adaptive mating method combining Hungarian mating schemes that have been previously suggested. Hungarian mating schemes include i) minimizing the sum of matching distances, ii) maximizing the sum, and iii) random matching. Our adaptive mating method selects one of the schemes with voting. Every matched pair of individuals has the right to vote for the mating scheme of the next generation. Its preference is closely related to the ratio of distance between parents over distance between parent and offspring.We apply the proposed method to well-known combinatorial optimization problems, the traveling salesman problem and the graph bisection problem. The proposed adaptive method showed better performance than any single Hungarian mating scheme and the nonadaptive hybrid scheme presented in previous work. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Association for Computing Machinery, Inc | - |
dc.relation.isPartOf | GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference | - |
dc.subject | Algorithms | - |
dc.subject | Combinatorial optimization | - |
dc.subject | Evolutionary algorithms | - |
dc.subject | Genetic algorithms | - |
dc.subject | Optimization | - |
dc.subject | Adaptive methods | - |
dc.subject | Combinatorial optimization problems | - |
dc.subject | Graph bisection | - |
dc.subject | Hybrid scheme | - |
dc.subject | Key operations | - |
dc.subject | Matching distances | - |
dc.subject | Mating schemes | - |
dc.subject | Random matching | - |
dc.subject | Traveling salesman problem | - |
dc.title | An adaptive method of Hungarian mating schemes in genetic algorithms | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.1145/2739482.2764669 | - |
dc.identifier.bibliographicCitation | GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, pp.1413 - 1414 | - |
dc.identifier.scopusid | 2-s2.0-84959420764 | - |
dc.citation.endPage | 1414 | - |
dc.citation.startPage | 1413 | - |
dc.citation.title | GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference | - |
dc.contributor.affiliatedAuthor | Yoon, Y. | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Genetic algorithm | - |
dc.subject.keywordAuthor | Mating scheme | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Combinatorial optimization | - |
dc.subject.keywordPlus | Evolutionary algorithms | - |
dc.subject.keywordPlus | Genetic algorithms | - |
dc.subject.keywordPlus | Optimization | - |
dc.subject.keywordPlus | Adaptive methods | - |
dc.subject.keywordPlus | Combinatorial optimization problems | - |
dc.subject.keywordPlus | Graph bisection | - |
dc.subject.keywordPlus | Hybrid scheme | - |
dc.subject.keywordPlus | Key operations | - |
dc.subject.keywordPlus | Matching distances | - |
dc.subject.keywordPlus | Mating schemes | - |
dc.subject.keywordPlus | Random matching | - |
dc.subject.keywordPlus | Traveling salesman problem | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.