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Cost Reduction of Traveling Salesman Problem with an Enhanced Genetic Algorithm

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  • K. B. Ishola

    (Department of Computer Science, Federal University of Lafia, P.M.B 146 Lafia, Nigeria)

  • O. E. James

    (Department of Computer Science, Federal University of Lafia, P.M.B 146 Lafia, Nigeria)

Abstract

Traveling Salesman Problem is a variation of NP hard problem and that has made it an interesting and challenging problem in the field of computer science, even though many techniques have been proposed to improve the performance of TSP. Genetic Algorithm is a technique used in computing to search the optimal solution from a various possible solution to a computational problem in order that maximizes or minimizes a particular function and Travelling Salesman Problem (TSP) is computational optimization problem. The time to solve TSP grows exponentially as the number of cities increases; if it is to be solved within a reasonable amount of time then it requires optimal solution. This research work examines the solution to improve the performance of TSP by coding it into a genetic form. The aim of this research work is to use the modified elements of Genetic Algorithm such as chromosomes, selection, crossover, mutation and fitness function to solve the Travelling Salesman Problem where one has to find the shortest or efficient route among the cities from the origin.

Suggested Citation

  • K. B. Ishola & O. E. James, 2020. "Cost Reduction of Traveling Salesman Problem with an Enhanced Genetic Algorithm," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 7(1), pages 110-117, January.
    • Handle: RePEc:bjc:journl:v:7:y:2020:i:1:p:110-117
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