Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms

Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms

This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. The three techniques have been applied successfully to solve th...

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Main Authors: Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad
Format: Article
Language:English
Published: IDOSI Publication 2016
Subjects:
QA76 Computer software
Online Access:http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/1/Solving%20Traveling%20Salesman%E2%80%99s%20Problem%20Using%20African%20Buffalo%20Optimization.pdf
id ump-14408
recordtype eprints
spelling ump-144082017-08-15T04:37:32Z http://umpir.ump.edu.my/id/eprint/14408/ Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms Odili, Julius Beneoluchi M. N. M., Kahar Noraziah, Ahmad QA76 Computer software This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. The three techniques have been applied successfully to solve the popular problem of an anonymous travelling salesman who is searching for the most optimized route to visiting all his customers in different locations of a large city or in a number of cities. This study focusses on these three methods with the aim of ascertaining the most efficient and effective. Results obtained from using these algorithms to solve the benchmark dataset on TSP available in TSPLIB95 serve as the comparative data. The outcome of this experiment shows that the newly-developed African Buffalo Optimization has very encouraging performance in terms of capacity to obtain optimal or near-optimal results consistently and in the most cost-effective manner. IDOSI Publication 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14408/1/Solving%20Traveling%20Salesman%E2%80%99s%20Problem%20Using%20African%20Buffalo%20Optimization.pdf Odili, Julius Beneoluchi and M. N. M., Kahar and Noraziah, Ahmad (2016) Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms. World Applied Sciences Journal, 34 (7). pp. 911-916. ISSN 1818-4952 http://idosi.org/wasj/wasj34(7)16/10.pdf DOI: 10.5829/idosi.wasj.2016.34.7.329
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
description This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. The three techniques have been applied successfully to solve the popular problem of an anonymous travelling salesman who is searching for the most optimized route to visiting all his customers in different locations of a large city or in a number of cities. This study focusses on these three methods with the aim of ascertaining the most efficient and effective. Results obtained from using these algorithms to solve the benchmark dataset on TSP available in TSPLIB95 serve as the comparative data. The outcome of this experiment shows that the newly-developed African Buffalo Optimization has very encouraging performance in terms of capacity to obtain optimal or near-optimal results consistently and in the most cost-effective manner.
format Article
author Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
author_facet Odili, Julius Beneoluchi
M. N. M., Kahar
Noraziah, Ahmad
author_sort Odili, Julius Beneoluchi
title Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
title_short Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
title_full Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
title_fullStr Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
title_full_unstemmed Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms
title_sort solving traveling salesman’s problem using african buffalo optimization, honey bee mating optimization & lin-kerninghan algorithms
publisher IDOSI Publication
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/
http://umpir.ump.edu.my/id/eprint/14408/1/Solving%20Traveling%20Salesman%E2%80%99s%20Problem%20Using%20African%20Buffalo%20Optimization.pdf
first_indexed 2023-09-18T22:18:07Z
last_indexed 2023-09-18T22:18:07Z
_version_ 1777415474632458240

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