Meta Heuristic Optimization of TSP using Genetic Algorithm
Richa Singh, Suraiya Parveen, Aparna · International Journal of Advance Research and Innovation · 2014
Initiation of this paper demarcates the limits of artificial intelligence, as it calls artificial intelligence a science for its extensibility and genetic algorithm to provide an affable decision to solve a popular routing problem named as Travelling Salesman Problem. This study will help more in moving to a world where a computer will be able to program based on natural selection and evolution. The travelling salesperson (or, salesman) problem (TSP) is an important combinatorial optimization problem. A combinatorial optimization problem helps to find an optimal object from a finite set of objects which does not follows an exhaustive search but the set of feasible solution is discrete. TSP aims to find the shortest path that travels through every city in a provided set of cities exactly once and travels back to the initial city using genetic algorithm. TSP is complex as it is a NP-complete problem. This literature proposes a heuristic approach for solving TSP: To find shortest path that travels through every city in a provided set of cities exactly once and travels back to the initial city. Proposed solution will provide a faster solution but not necessarily an optimal solution.