New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]

New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]

The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization problem. The goal is to find the shortest distance tour that visits each city in a given list exactly once and then returns to the starting city. TSP is an NP-complete problem that has many interaction var...

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Main Authors: Alias, Fadzilawani Astifar, Shamsuddin, Maisurah, Mohamed, Siti Asmah, Mahlan, Siti Balqis
Format: Article
Language:English
Published: Universiti Teknologi MARA, Pulau Pinang 2015
Subjects:
Analysis
Online Access:http://ir.uitm.edu.my/id/eprint/11988/
http://ir.uitm.edu.my/id/eprint/11988/1/AJ_FADZILAWANI%20ASTIFAR%20ALIAS%20EAJ%2015.pdf
id uitm-11988
recordtype eprints
spelling uitm-119882016-07-20T03:04:38Z http://ir.uitm.edu.my/id/eprint/11988/ New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.] Alias, Fadzilawani Astifar Shamsuddin, Maisurah Mohamed, Siti Asmah Mahlan, Siti Balqis Analysis The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization problem. The goal is to find the shortest distance tour that visits each city in a given list exactly once and then returns to the starting city. TSP is an NP-complete problem that has many interaction variables with a high degree of freedom. The main objective of TSP is to determine the network route to minimize the total distance, cost or time. In this research, the heuristic method called Genetic Algorithm (GA) is used to solve the TSP. GA is a system developing methods that uses the natural principle of a genetic population and involves three main processes that are crossover, mutation and inversion. GA is implemented with some new operators called Nearest Fragment (NF) and Modified Order Crossover (MOC). GA implementation on TSP is done by using Microsoft C++ Programming. Solutions to the problem are presented and performance comparison is described with the existing best solution. Universiti Teknologi MARA, Pulau Pinang 2015 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/11988/1/AJ_FADZILAWANI%20ASTIFAR%20ALIAS%20EAJ%2015.pdf Alias, Fadzilawani Astifar and Shamsuddin, Maisurah and Mohamed, Siti Asmah and Mahlan, Siti Balqis (2015) New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]. Esteem Academic Journal, 11 (1). pp. 127-134. ISSN 1675-7939
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
topic Analysis
spellingShingle Analysis
Alias, Fadzilawani Astifar
Shamsuddin, Maisurah
Mohamed, Siti Asmah
Mahlan, Siti Balqis
New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
description The Travelling Salesman Problem (TSP) is a well-known and important combinatorial optimization problem. The goal is to find the shortest distance tour that visits each city in a given list exactly once and then returns to the starting city. TSP is an NP-complete problem that has many interaction variables with a high degree of freedom. The main objective of TSP is to determine the network route to minimize the total distance, cost or time. In this research, the heuristic method called Genetic Algorithm (GA) is used to solve the TSP. GA is a system developing methods that uses the natural principle of a genetic population and involves three main processes that are crossover, mutation and inversion. GA is implemented with some new operators called Nearest Fragment (NF) and Modified Order Crossover (MOC). GA implementation on TSP is done by using Microsoft C++ Programming. Solutions to the problem are presented and performance comparison is described with the existing best solution.
format Article
author Alias, Fadzilawani Astifar
Shamsuddin, Maisurah
Mohamed, Siti Asmah
Mahlan, Siti Balqis
author_facet Alias, Fadzilawani Astifar
Shamsuddin, Maisurah
Mohamed, Siti Asmah
Mahlan, Siti Balqis
author_sort Alias, Fadzilawani Astifar
title New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
title_short New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
title_full New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
title_fullStr New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
title_full_unstemmed New genetic operator for solving the travelling salesman problem / Fadzilawani Astifar Alias ... [et al.]
title_sort new genetic operator for solving the travelling salesman problem / fadzilawani astifar alias ... [et al.]
publisher Universiti Teknologi MARA, Pulau Pinang
publishDate 2015
url http://ir.uitm.edu.my/id/eprint/11988/
http://ir.uitm.edu.my/id/eprint/11988/1/AJ_FADZILAWANI%20ASTIFAR%20ALIAS%20EAJ%2015.pdf
first_indexed 2023-09-18T22:48:48Z
last_indexed 2023-09-18T22:48:48Z
_version_ 1777417404937142272

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