Open AccessSolving Random Travelling Salesman Problem using Firefly Algorithm
Author(s) -
Nitesh M. Sureja
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c9113.029420
Subject(s) - firefly algorithm , travelling salesman problem , simulated annealing , ant colony optimization algorithms , algorithm , mathematical optimization , computer science , genetic algorithm , convergence (economics) , population based incremental learning , extremal optimization , meta optimization , 2 opt , optimization problem , mathematics , particle swarm optimization , economics , economic growth
The firefly algorithm is a recently developed optimization algorithm, which is suitable for solving any kind of discrete optimization problems. This is an algorithm inspired from the nature. In this paper, a firefly algorithm is proposed to solve random traveling salesman problem. The solution to this problem is already proposed by the algorithms like simulated annealing, genetic algorithms and ant colony algorithms. This algorithm is developed to deal with the issue of accuracy and convergence rate in the solutions provided by those algorithms. A comparison of the results produced by proposed algorithm with the results of simulated annealing, genetic algorithms and ant colony algorithm is given. Finally, the effectiveness of the proposed algorithm is discussed.