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World Journal of Engineering
Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

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Abstract

IMPROVED GENETIC ALGORITHM USING HYBRID INITIAL POPULATION TO SOLVE TRAVELLING SALESMAN PROBLEM

Pratha Deewan*, Punit Kumar and Vinod Todwal

ABSTRACT

Genetic Algorithm is very useful to solve optimization problems. It performs genetic operators to solve optimization problems. Travelling Salesman Problem is a well-known optimization problem. TSP is useful to solve many problems of science and engineering. In this paper genetic algorithm is applied to solve TSP. A hybrid initial population is generated in genetic algorithm. The hybridization of initial population improves the performance of the genetic algorithm. Proposed genetic algorithm is applied on three standard instances of TSP and results are compared with other heuristic algorithms. From the experimental results it is observed that the proposed hybrid GA performs better than other techniques.

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