Genetic Algorithms Dynamic Population Size with Cloning in Solving Traveling Salesman Problem

Authors

  • Erna Budhiarti Nababan Universitas Sumatera Utara
  • Opim Salim Sitompul Universitas Sumatera Utara
  • Yuni Cancer Universitas Sumatera Utara

DOI:

https://doi.org/10.32734/jocai.v2.i2-326

Keywords:

population size, local optimum, early convergence, salem, travelling salesman problem

Abstract

Population size of classical genetic algorithm is determined constantly. Its size remains constant over the run. For more complex problems, larger population sizes need to be avoided from early convergence to produce local optimum. Objective of this research is to evaluate population resizing i.e. dynamic population sizing for Genetic Algorithm (GA) using cloning strategy. We compare performance of proposed method and traditional GA employed to Travelling Salesman Problem (TSP) of A280.tsp taken from TSPLIB. Result shown that GA with dynamic population size exceed computational time of traditional GA.

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Published

2018-08-03

How to Cite

Nababan, E. B., Sitompul, O. S., & Cancer, Y. (2018). Genetic Algorithms Dynamic Population Size with Cloning in Solving Traveling Salesman Problem. Data Science: Journal of Computing and Applied Informatics, 2(2), 87-100. https://doi.org/10.32734/jocai.v2.i2-326

Issue

Vol. 2 No. 2 (2018): Data Science: Journal of Computing and Applied Informatics (JoCAI)

Section

Articles

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