Integrating Grasshopper Optimization Algorithm with Local Search for Solving Data Clustering Problems

Authors

M. A. El-Shorbagy^{1, 2, *,} , A. Y. Ayoub²

¹Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia

²Department of Basic Engineering Science, Faculty of Engineering, Shebin El-Kom, Menoufia University, Egypt

^*Corresponding author. Email: mohammed_shorbagy@yahoo.com

DOI

10.2991/ijcis.d.210203.008How to use a DOI?

Keywords

Data clustering problems; grasshopper optimization algorithm; local search; optimization; swarm intelligence algorithms

Abstract

This paper proposes a hybrid approach for solving data clustering problems. This hybrid approach used one of the swarm intelligence algorithms (SIAs): grasshopper optimization algorithm (GOA) due to its robustness and effectiveness in solving optimization problems. In addition, a local search (LS) strategy is applied to enhance the solution quality and access to optimal data clustering. The proposed algorithm is divided into two stages, the first of which aims to use GOA to prevent getting trapped in local minima and to find an approximate solution. While the second stage aims by LS to increase LS performance and obtain the best optimal solution. In other words, the proposed algorithm combines the exploitation capability of GOA and the discovery capability of LS, and integrates the merits of both GOA and LS. In addition, 7 well-known datasets that commonly used in several studies are used to validate the proposed technique. The results of the proposed methodology are compared to previous studies; where statistical analysis, for the various algorithms, indicated the superiority of the proposed methodology over other algorithms and its ability to solve this type of problem.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - M. A. El-Shorbagy
AU  - A. Y. Ayoub
PY  - 2021
DA  - 2021/02/12
TI  - Integrating Grasshopper Optimization Algorithm with Local Search for Solving Data Clustering Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 783
EP  - 793
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210203.008
DO  - 10.2991/ijcis.d.210203.008
ID  - El-Shorbagy2021
ER  -