A novel discrete Rat swarm optimization (DRSO) algorithm for solving the traveling salesman problem

Authors

  • Toufik Mzili Department of Computer Science, Laboratory LAROSERI, Faculty of Science, Chouaib Doukkali University, Morocco
  • Mohammed Essaid Riffi Department of Computer Science, Laboratory LAROSERI, Faculty of Science, Chouaib Doukkali University, Morocco
  • Ilyass Mzili Department of Computer Science, Laboratory LAROSERI, Faculty of Science, Chouaib Doukkali University, Morocco
  • Gaurav Dhiman Department of Computer Science, Government Bikram College of Commerce, Punjab, India

DOI:

https://doi.org/10.31181/dmame0318062022m

Keywords:

Travelling Salesman Problem, Rat swarm Optimization, Combinatorial optimization, Metaheuristic, Nature-inspired, PSO

Abstract

Metaheuristics are often used to find solutions to real and complex problems. These algorithms can solve optimization problems and provide solutions close to the global optimum in an acceptable and reasonable time. In this paper, we will present a new bio-inspired metaheuristic based on the natural chasing and attacking behaviors of rats in nature, called Rat swarm optimizer. Which has given good results in solving several continuous optimization problems, and adapted it to solve a discrete, NP-hard, and classical optimization problem that is the traveling salesman problem (TSP) while respecting the natural behavior of rats. To test the efficiency of the adaptation of our proposal, we applied the adapted rat swarm optimization (RSO) algorithm on some reference instances of TSPLIB. The obtained results show the performance of the proposed method in solving the traveling salesman problem (TSP).

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Published

2022-06-18

How to Cite

Mzili , T., Riffi , M. E., Mzili, I., & Dhiman, G. (2022). A novel discrete Rat swarm optimization (DRSO) algorithm for solving the traveling salesman problem. Decision Making: Applications in Management and Engineering, 5(2), 287–299. https://doi.org/10.31181/dmame0318062022m

Issue

Vol. 5 No. 2 (2022): Decision Making: Applications in Management and Engineering

Section

Regular articles

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Copyright (c) 2022 Decision Making: Applications in Management and Engineering

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