Discrete Starfish Optimization Algorithm for Symmetric Travelling Salesman Problem

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dc.authoridK�l��, Fatih/0000-0002-8550-1562
dc.authoridAKTAS, MUHAMMET/0000-0002-2598-3387
dc.contributor.authorAktas, Muhammet
dc.contributor.authorKilic, Fatih
dc.date.accessioned2026-02-27T07:32:50Z
dc.date.available2026-02-27T07:32:50Z
dc.date.issued2025
dc.description.abstractThis paper introduces a new discrete StarFish Optimization Algorithm (D-SFOA) to solve a complex discrete Symmetric Travelling Salesman Problem (STSP). The discrete SFOA algorithm is initialized with the initial population of classical SFOA, and the continuous values of the individuals in the population are converted to the discrete version using the random key method. Ten neighbourhood methods used in this study provide diversity to the starfish population, and the 2-opt local search algorithm allows the study to find shorter tours. The performance of D-SFOA is tested on STSP samples ranging in size from 30 to 1084 from TSPLIB. Discrete versions of the Grey Wolf Optimizer (D-GWO) and Harris Hawk Optimization (D-HHO) algorithms are applied with the same parameters to compare the performance of the proposed algorithm. The algorithm uses descriptive statistics such as average tour, best tour, percentage of deviation of the mean tour, percentage of deviation of the best tour, and execution time to ensure a fair comparison. The Wilcoxon signed-rank test and Ablation test are applied to measure the significant difference in the values of the algorithms and to observe the performance effect of the main components used in the proposed algorithm on tour length and execution time, respectively. This study's numerical and statistical results show that D-SFOA has significantly outperformed other alternative algorithms and provided better solutions than the best-known solution.
dc.identifier.doi10.1109/ACCESS.2025.3579248
dc.identifier.endpage102687
dc.identifier.issn2169-3536
dc.identifier.startpage102675
dc.identifier.urihttp://dx.doi.org/10.1109/ACCESS.2025.3579248
dc.identifier.urihttps://hdl.handle.net/20.500.14669/4357
dc.identifier.volume13
dc.identifier.wosWOS:001511065700014
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIEEEAccess
dc.relation.publicationcategoryMakale - Uluslararas� Hakemli Dergi - Kurum ��retim Eleman�
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20260302
dc.subjectUrban areas
dc.subjectDrones
dc.subjectCosts
dc.subjectSoftware algorithms
dc.subjectMathematical models
dc.subjectGenetic algorithms
dc.subjectClassification algorithms
dc.subjectSearch problems
dc.subjectCombinatorial optimization
dc.subjectmetaheuristic
dc.subjectrandom key method
dc.subjectstarfish optimization algorithm
dc.subjecttravelling salesman problem
dc.subject2-opt algorithm
dc.subjecttravelling salesman problem
dc.subject2-opt algorithm
dc.titleDiscrete Starfish Optimization Algorithm for Symmetric Travelling Salesman Problem
dc.typeArticle

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