ABSTRACT

Solving NP hard problem like Travelling Salesman Problem (TSP) is a major challenge faced by analysts even though many techniques are available. Many versions of Genetic Algorithms are introduced by researchers to improve its performance in solving TSP. Clustering Genetic Algorithm (CGA) was recently introduced and this paper analyzes the results obtained by implementing it for TSP. It is observed that CGA effectively finds out more optimal solution sooner than the Standard Genetic Algorithm (SGA) in 3 different instances considered.