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An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints
Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948472/ https://www.ncbi.nlm.nih.gov/pubmed/24701158 http://dx.doi.org/10.1155/2014/313767 |
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author | Sung, Jinmo Jeong, Bongju |
author_facet | Sung, Jinmo Jeong, Bongju |
author_sort | Sung, Jinmo |
collection | PubMed |
description | Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments. |
format | Online Article Text |
id | pubmed-3948472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-39484722014-04-03 An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints Sung, Jinmo Jeong, Bongju ScientificWorldJournal Research Article Traveling sales man problem with precedence constraints is one of the most notorious problems in terms of the efficiency of its solution approach, even though it has very wide range of industrial applications. We propose a new evolutionary algorithm to efficiently obtain good solutions by improving the search process. Our genetic operators guarantee the feasibility of solutions over the generations of population, which significantly improves the computational efficiency even when it is combined with our flexible adaptive searching strategy. The efficiency of the algorithm is investigated by computational experiments. Hindawi Publishing Corporation 2014-02-17 /pmc/articles/PMC3948472/ /pubmed/24701158 http://dx.doi.org/10.1155/2014/313767 Text en Copyright © 2014 J. Sung and B. Jeong. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sung, Jinmo Jeong, Bongju An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title | An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title_full | An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title_fullStr | An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title_full_unstemmed | An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title_short | An Adaptive Evolutionary Algorithm for Traveling Salesman Problem with Precedence Constraints |
title_sort | adaptive evolutionary algorithm for traveling salesman problem with precedence constraints |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948472/ https://www.ncbi.nlm.nih.gov/pubmed/24701158 http://dx.doi.org/10.1155/2014/313767 |
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