Particle swarm optimisation algorithm for solving shortest path problems with mixed fuzzy arc weights

Abstract

Shortest path problem is one of the most fundamental components in the fields of transportation and communication networks. This paper concentrates on a shortest path problem on a network where arc weights are represented by different kinds of fuzzy numbers. Recently, a genetic algorithm has been proposed for finding the shortest path in a network with mixed fuzzy arc weights due to the complexity of the addition of various fuzzy numbers for larger problems. In this paper, a particle swarm optimisation (PSO) algorithm in fuzzy environment is used for the same due to its superior convergence speed. The main contribution of this paper is the reduction of the time complexity of the existing genetic algorithm. Additionally, to compare the obtained results of the proposed PSO algorithm with those of the existing algorithm, two shortest path problems having mixed fuzzy arc weights are solved. The comparative examples illustrate that the algorithm proposed in this paper is more efficient than the existing algorithm in terms of time complexity.