PSO Based Constraint Optimization of Intuitionistic Fuzzy Shortest Path Problem in an Undirected Network

Abstract

Shortest Path Problem (SPP) is mainly used in network optimization, which has a wide range of applications such as routing, scheduling, communication and transportation. The main objective of this work is to find the shortest path between two specified nodes by satisfying certain constraints. This modified version of SP is called Constraint Shortest Path (CSP) which establishes a certain limit on selected constraints for the path. The limit for constraint values is precisely specified in traditional CSP problems. But, the precise data may vary due to some reasons like environmental conditions, traffic and payload. That is why proposed CSP make use of intuitionistic fuzzy numbers to deal with these kinds of imprecise data. As well as, it is difficult to find an optimal solution in complex search space of an undirected network. Hence, Particle Swarm Optimization (PSO) is used in the proposed work to get the optimal global solution within feasible regions. A numerical example is also illustrated along with the implementation of proposed work in Matlab 2016a working environment.