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• W4207002264 abstract "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." @default.
• W4207002264 created "2022-01-26" @default.
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• W4207002264 date "2022-02-28" @default.
• W4207002264 modified "2023-10-16" @default.
• W4207002264 title "A hybrid genetic algorithm, list-based simulated annealing algorithm, and different heuristic algorithms for travelling salesman problem" @default.
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• W4207002264 doi "https://doi.org/10.1093/jigpal/jzac028" @default.
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