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Experimental study of a hybrid genetic algorithm for the multiple travelling salesman problem

Author name : MAHA ATA OMAIR ALFURHUD
Publication Date : 2020-01-09
Journal Name : hindawi

Abstract

The multiple travelling salesman problem (MTSP), an extension of the well-known travelling salesman problem (TSP), is studied
here. In MTSP, starting from a depot, multiple salesmen require to visit all cities so that each city is required to be visited only once
by one salesman only. It is NP-hard and is more complex than the usual TSP. So, exact optimal solutions can be obtained for
smaller sized problem instances only. For large-sized problem instances, it is essential to apply heuristic algorithms, and amongst
them, genetic algorithm is identified to be successfully deal with such complex optimization problems. So, we propose a hybrid
genetic algorithm (HGA) that uses sequential constructive crossover, a local search approach along with an immigration
technique to find high-quality solution to the MTSP. /en our proposed HGA is compared against some state-of-the-art al-
gorithms by solving some TSPLIB symmetric instances of several sizes with various number of salesmen. Our experimental
investigation demonstrates that the HGA is one of the best algorithms

Keywords

Keywords—Multiple travelling salesman problem; NP-hard; genetic algorithm; sequential constructive crossover; adaptive; greedy; comprehensive

Publication Link

https://onlinelibrary.wiley.com/doi/pdf/10.1155/2020/3431420

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