Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator
Joint Authors
Hussain, Ijaz
Shad, Muhammad Yousaf
Mohamd Shoukry, Alaa
Hussain, Abid
Nauman Sajid, M.
Gani, Showkat
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea.
These methods do not ensure optimal solutions; however, they give good approximation usually in time.
The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem.
The genetic algorithm depends on selection criteria, crossover, and mutation operators.
To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations.
In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance.
This approach has been linked with path representation, which is the most natural way to represent a legal tour.
Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements.
American Psychological Association (APA)
Hussain, Abid& Shad, Muhammad Yousaf& Nauman Sajid, M.& Hussain, Ijaz& Mohamd Shoukry, Alaa& Gani, Showkat. 2017. Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1141086
Modern Language Association (MLA)
Hussain, Abid…[et al.]. Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1141086
American Medical Association (AMA)
Hussain, Abid& Shad, Muhammad Yousaf& Nauman Sajid, M.& Hussain, Ijaz& Mohamd Shoukry, Alaa& Gani, Showkat. Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1141086
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141086