Publication:
Performance of Equilibrium Optimizer for the Traveling Salesman Problem

datacite.subject.fos oecd::Natural sciences::Mathematics
dc.contributor.author Quyen Nguyen
dc.contributor.author Minh-Phung Bui
dc.date.accessioned 2022-10-31T06:21:52Z
dc.date.available 2022-10-31T06:21:52Z
dc.date.issued 2021
dc.description.abstract This paper presents a new method based on Equilibrium Optimizer (EO) algorithm that is inspired from the mass balance of a control volume for traveling salesman problem (TSP). For enhancing the efficiency of EO, the 2- opt movement algorithm is used to update the solution generated by EO. The efficiency of the proposed EO for the TSP problem has been compared with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) on different instances consisting of the 14-city, 30-city, 48-city and 52-city. The calculated results show that for the large scale instances such as 48-city and 52-city, EO has found the better tour than PSO. In comparison with GA, EO has ability finding the best tour with the smaller mean and standard deviation. The comparisons with previous methods in literature have also demonstrated that EO has ability to search the better tour than other methods. Thus, the proposed EO can be a potential method for the TSP problem.
dc.identifier.doi 10.22266/ijies2021.1031.05
dc.identifier.uri http://repository.vlu.edu.vn:443/handle/123456789/391
dc.language.iso en_US
dc.relation.ispartof International Journal of Intelligent Engineering and Systems
dc.relation.issn 2185-3118
dc.subject "Equilibrium optimizer
dc.subject Genetic algorithm
dc.subject Particle swarm optimization
dc.subject Traveling salesman problem
dc.subject 2- opt."
dc.title Performance of Equilibrium Optimizer for the Traveling Salesman Problem
dc.type journal-article
dspace.entity.type Publication
oaire.citation.issue 5
oaire.citation.volume 14
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