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

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

Erna Budhiarti Nababan (Universitas Sumatera Utara)
Opim Salim Sitompul (Universitas Sumatera Utara)
Yuni Cancer (Universitas Sumatera Utara)

Article Info

Publish Date
03 Aug 2018

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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Journal Info
Data Science: Journal of Computing and Applied Informatics
Website

Abbrev

JoCAI

Publisher

Universitas Sumatera Utara

Subject

Computer Science & IT

Description

Data Science: Journal of Computing and Applied Informatics (JoCAI) is a peer-reviewed biannual journal (January and July) published by TALENTA Publisher and organized by Faculty of Computer Science and Information Technology, Universitas Sumatera Utara (USU) as an open access journal. It welcomes ...