Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After criti...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis
2017
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/18345/1/Performance%20Analyses%20of%20Nature-inspired%20Algorithms1.pdf |
| _version_ | 1825823855991586816 |
|---|---|
| author | Julius, Beneoluchi Odili M. N. M., Kahar Noraziah, Ahmad M., Zarina Riaz, Ul Haq |
| author_facet | Julius, Beneoluchi Odili M. N. M., Kahar Noraziah, Ahmad M., Zarina Riaz, Ul Haq |
| author_sort | Julius, Beneoluchi Odili |
| collection | UMP |
| description | This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. The study reveals that the African Buffalo Optimization and the Ant Colony Optimization are the best in solving the symmetric TSP, which is similar to intelligence gathering channel in the strategic management of big organizations, while the Randomized Insertion Algorithm holds the best promise in asymmetric TSP instances akin to strategic information exchange channels in strategic management. |
| first_indexed | 2024-03-06T12:17:20Z |
| format | Article |
| id | UMPir18345 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:17:20Z |
| publishDate | 2017 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | UMPir183452018-09-12T07:56:52Z http://umpir.ump.edu.my/id/eprint/18345/ Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management Julius, Beneoluchi Odili M. N. M., Kahar Noraziah, Ahmad M., Zarina Riaz, Ul Haq QA76 Computer software This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. The study reveals that the African Buffalo Optimization and the Ant Colony Optimization are the best in solving the symmetric TSP, which is similar to intelligence gathering channel in the strategic management of big organizations, while the Randomized Insertion Algorithm holds the best promise in asymmetric TSP instances akin to strategic information exchange channels in strategic management. Taylor & Francis 2017-06 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/18345/1/Performance%20Analyses%20of%20Nature-inspired%20Algorithms1.pdf Julius, Beneoluchi Odili and M. N. M., Kahar and Noraziah, Ahmad and M., Zarina and Riaz, Ul Haq (2017) Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management. Intelligent Automation & Soft Computing. pp. 1-11. ISSN 1079-8587. (In Press / Online First) (In Press / Online First) http://www.tandfonline.com/doi/abs/10.1080/10798587.2017.1334370 DOI: 10.1080/10798587.2017.1334370 |
| spellingShingle | QA76 Computer software Julius, Beneoluchi Odili M. N. M., Kahar Noraziah, Ahmad M., Zarina Riaz, Ul Haq Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title | Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title_full | Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title_fullStr | Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title_full_unstemmed | Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title_short | Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management |
| title_sort | performance analyses of nature inspired algorithms on the traveling salesman s problems for strategic management |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/18345/1/Performance%20Analyses%20of%20Nature-inspired%20Algorithms1.pdf |
| work_keys_str_mv | AT juliusbeneoluchiodili performanceanalysesofnatureinspiredalgorithmsonthetravelingsalesmansproblemsforstrategicmanagement AT mnmkahar performanceanalysesofnatureinspiredalgorithmsonthetravelingsalesmansproblemsforstrategicmanagement AT noraziahahmad performanceanalysesofnatureinspiredalgorithmsonthetravelingsalesmansproblemsforstrategicmanagement AT mzarina performanceanalysesofnatureinspiredalgorithmsonthetravelingsalesmansproblemsforstrategicmanagement AT riazulhaq performanceanalysesofnatureinspiredalgorithmsonthetravelingsalesmansproblemsforstrategicmanagement |