A hybrid genetic algorithm, list-based simulated annealing algorithm, and different heuristic algorithms for the travelling salesman problem

Abstract The travelling salesman problem (TSP) belongs to the class of NP-hard problems, in which an optimal solution to the problem cannot be obtained within a reasonable computational time for large-sized problems. To address TSP, we propose a hybrid algorithm, called GA-TCTIA-LBSA, in which a gen...

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Veröffentlicht in:Logic journal of the IGPL 2023-07, Vol.31 (4), p.602-617
Hauptverfasser: Ilin, Vladimir, Simić, Dragan, Simić, Svetislav D, Simić, Svetlana, Saulić, Nenad, Calvo-Rolle, José Luis
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract The travelling salesman problem (TSP) belongs to the class of NP-hard problems, in which an optimal solution to the problem cannot be obtained within a reasonable computational time for large-sized problems. To address TSP, we propose a hybrid algorithm, called GA-TCTIA-LBSA, in which a genetic algorithm (GA), tour construction and tour improvement algorithms (TCTIAs) and a list-based simulated annealing (LBSA) algorithm are used. The TCTIAs are introduced to generate a first population, and after that, a search is continued with the GA. The problem of premature convergence of the GA to local optimum is tackled by a method called social disaster technique. Afterwards, the LBSA is applied to generate a new population based on one of two proposed operators called packing and judgement day. The proposed algorithm is implemented in the MATLAB environment, and its two variants, called GA-TCTIA-LBSA packing and GA-TCTIA-LBSA judgement day, are tested on symmetric and asymmetric instances from TSPLIB. The overall results demonstrate that the proposed GA-TCTIA-LBSAs offer promising results, particularly for small-sized instances.
ISSN:1367-0751
1368-9894
DOI:10.1093/jigpal/jzac028