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

Data Science: Journal of Computing and Applied Informatics

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Field Value
 
Title Genetic Algorithms Dynamic Population Size with Cloning in Solving Traveling Salesman Problem
 
Creator Nababan, Erna Budhiarti
Sitompul, Opim Salim
Cancer, Yuni
 
Description 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.
 
Publisher Talenta Publisher
 
Date 2018-08-03
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://talenta.usu.ac.id/index.php/JoCAI/article/view/326
10.32734/jocai.v2.i2-326
 
Source Data Science: Journal of Computing and Applied Informatics; Vol 2 No 2 (2018): Data Science: Journal of Computing and Applied Informatics (JoCAI); 87-100
2580-829X
2580-6769
 
Language eng
 
Relation https://talenta.usu.ac.id/index.php/JoCAI/article/view/326/178
 
Rights Copyright (c) 2018 Data Science: Journal of Computing and Applied Informatics
 

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