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A novel discrete bat algorithm for solving the travelling salesman problem

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Abstract

The travelling salesman problem (TSP) is one of the well-known NP-hard combinatorial optimization and extensively studied problems in discrete optimization. The bat algorithm is a new nature-inspired metaheuristic optimization algorithm introduced by Yang in 2010, especially based on echolocation behavior of microbats when searching their prey. Firstly, this algorithm is used to solve various continuous optimization problems. In this paper we extend a discrete bat-inspired algorithm to solve the famous TSP. Although many algorithms have been used to solve TSP, the main objective of this research is to investigate this discrete version to achieve significant improvements, not only compared to traditional algorithms but also to another metaheuristics. Moreover, this study is based on a benchmark dataset of symmetric TSP from TSPLIB library.

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Authors and Affiliations

  1. LAROSERI Laboratory, Department of Computer Science, Faculty of Science, Chouaïb Doukkali University, Route Ben Maachou, 24000, El Jadida, Morocco

    Yassine Saji & Mohammed Essaid Riffi

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  1. Yassine Saji
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  2. Mohammed Essaid Riffi
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Correspondence to Yassine Saji.

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Saji, Y., Riffi, M.E. A novel discrete bat algorithm for solving the travelling salesman problem. Neural Comput & Applic 27, 1853–1866 (2016). https://doi.org/10.1007/s00521-015-1978-9

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