The Best Efficient Solutions for Multi-Criteria Travelling Salesman Problem Using Local Search Methods

Authors

  • Manal Ghassan Ahmed Mathematics Department, College of Science, Mustansiriyah University, Baghdad, Iraq
  • Faez Hassan Ali Mathematics Department, College of Science, Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2022.63.10.21

Keywords:

Travelling Salesman Problem, Local Search Method, Particle Swarm Optimization, Bees Algorithm

Abstract

     In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for  jobs in a reasonable time.

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Published

2022-10-30

How to Cite

Ahmed, M. G., & Ali, F. H. (2022). The Best Efficient Solutions for Multi-Criteria Travelling Salesman Problem Using Local Search Methods. Iraqi Journal of Science, 63(10), 4352–4360. https://doi.org/10.24996/ijs.2022.63.10.21

Issue

Section

Mathematics