Genetic algorithm to optimize routing problem modelled as the travelling salesman problem

This study presents genetic algorithm (GA) to solve routing problem modelled as the travelling salesman problem (TSP). Genetic algorithm conceptually follows steps inspired by the biological process of evolution. GA is following the ideas of "survival of the fittest" which meant better...

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Main Author:	Muhammad Azrul Faiz , Nor Adzmi
Format:	Undergraduates Project Papers
Language:	English
Published:	2013
Subjects:	T Technology (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/7666/ http://umpir.ump.edu.my/id/eprint/7666/ http://umpir.ump.edu.my/id/eprint/7666/1/MUHAMMAD_AZRUL_FAIZ_BIN_NOR_ADZMI.PDF

id	ump-7666
recordtype	eprints
spelling	ump-76662015-03-03T09:37:23Z http://umpir.ump.edu.my/id/eprint/7666/ Genetic algorithm to optimize routing problem modelled as the travelling salesman problem Muhammad Azrul Faiz , Nor Adzmi T Technology (General) This study presents genetic algorithm (GA) to solve routing problem modelled as the travelling salesman problem (TSP). Genetic algorithm conceptually follows steps inspired by the biological process of evolution. GA is following the ideas of "survival of the fittest" which meant better and better solution evolves from previous generations until a near optimal solution is obtained. In TSP, There are cities and distance given between the cities. The salesman needs to visit all the cities, but does not to travel so much. This study will use PCB component placement which is modelled as TSP. The objective is to find the sequence of the routing in order to minimize travelling distance. The GA with Roulette wheel selection, linear order crossover and inversion mutation is used in the study. The computational experiment was done using several randomly generated data with different GA parameter setting. The optimal distance obtains for 40 component placements is 8.9861 mm within 6.751 seconds The results from the experiments show that GA used in this study is effective to solve PCB component placement which is modelled as TSP. 2013-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7666/1/MUHAMMAD_AZRUL_FAIZ_BIN_NOR_ADZMI.PDF Muhammad Azrul Faiz , Nor Adzmi (2013) Genetic algorithm to optimize routing problem modelled as the travelling salesman problem. Faculty of Manufacturing Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:78505&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Muhammad Azrul Faiz , Nor Adzmi Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
description	This study presents genetic algorithm (GA) to solve routing problem modelled as the travelling salesman problem (TSP). Genetic algorithm conceptually follows steps inspired by the biological process of evolution. GA is following the ideas of "survival of the fittest" which meant better and better solution evolves from previous generations until a near optimal solution is obtained. In TSP, There are cities and distance given between the cities. The salesman needs to visit all the cities, but does not to travel so much. This study will use PCB component placement which is modelled as TSP. The objective is to find the sequence of the routing in order to minimize travelling distance. The GA with Roulette wheel selection, linear order crossover and inversion mutation is used in the study. The computational experiment was done using several randomly generated data with different GA parameter setting. The optimal distance obtains for 40 component placements is 8.9861 mm within 6.751 seconds The results from the experiments show that GA used in this study is effective to solve PCB component placement which is modelled as TSP.
format	Undergraduates Project Papers
author	Muhammad Azrul Faiz , Nor Adzmi
author_facet	Muhammad Azrul Faiz , Nor Adzmi
author_sort	Muhammad Azrul Faiz , Nor Adzmi
title	Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
title_short	Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
title_full	Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
title_fullStr	Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
title_full_unstemmed	Genetic algorithm to optimize routing problem modelled as the travelling salesman problem
title_sort	genetic algorithm to optimize routing problem modelled as the travelling salesman problem
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/7666/ http://umpir.ump.edu.my/id/eprint/7666/ http://umpir.ump.edu.my/id/eprint/7666/1/MUHAMMAD_AZRUL_FAIZ_BIN_NOR_ADZMI.PDF
first_indexed	2023-09-18T22:04:31Z
last_indexed	2023-09-18T22:04:31Z
_version_	1777414618289799168

Genetic algorithm to optimize routing problem modelled as the travelling salesman problem

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