A clustering-based visual analysis tool for Genetic Algorithm

Daneshpajouh, H. and Zakaria, N. (2017) A clustering-based visual analysis tool for Genetic Algorithm. In: UNSPECIFIED.

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Abstract

While Genetic Algorithm (GA) is a powerful tool for combinatorial optimization, the vast population of candidate solutions it typically deploys and algorithm's intrinsic randomness lead to difficulty in understanding its search behavior. We discuss in this paper a clustering-based visualization tool for GA that attempts to mediate this problem. GA population across its entire generations are clustered, and each cluster and its individuals are mapped to a visual symbol. The tool enables a GA researcher or user to understand better the behavior of a GA run, specifically the local searches it performs in its global exploration to go from one generation to another. Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 4; Conference of 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 ; Conference Date: 27 February 2017 Through 1 March 2017; Conference Code:134874
Uncontrolled Keywords: Clustering algorithms; Combinatorial optimization; Computer graphics; Computer vision; Visualization, Cluster formations; Evolutionary process; Global exploration; Intrinsic randomness; Search behavior; Search spaces; Visual analysis; Visualization tools, Genetic algorithms
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:21
Last Modified: 09 Nov 2023 16:21
URI: https://khub.utp.edu.my/scholars/id/eprint/9055

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