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PSO-based group-oriented crow search algorithm (PGCSA)

Sudeepa Das (Department of Information Technology, National Institute of Technology, Raipur, India)
Tirath Prasad Sahu (Department of Information Technology, National Institute of Technology, Raipur, India)
Rekh Ram Janghel (Department of Information Technology, National Institute of Technology, Raipur, India)

Engineering Computations

ISSN: 0264-4401

Article publication date: 20 November 2020

Issue publication date: 8 February 2021

201

Abstract

Purpose

The purpose of this paper is to modify the crow search algorithm (CSA) to enhance both exploration and exploitation capability by including two novel approaches. The positions of the crows are updated in two approaches based on awareness probability (AP). With AP, the position of a crow is updated by considering its velocity, calculated in a similar fashion to particle swarm optimization (PSO) to enhance the exploiting capability. Without AP, the crows are subdivided into groups by considering their weights, and the crows are updated by conceding leaders of the groups distributed over the search space to enhance the exploring capability. The performance of the proposed PSO-based group-oriented CSA (PGCSA) is realized by exploring the solution of benchmark equations. Further, the proposed PGCSA algorithm is validated over recently published algorithms by solving engineering problems.

Design/methodology/approach

In this paper, two novel approaches are implemented in two phases of CSA (with and without AP), which have been entitled the PGCSA algorithm to solve engineering benchmark problems.

Findings

The proposed algorithm is applied with two types of problems such as eight benchmark equations without constraint and six engineering problems.

Originality/value

The PGCSA algorithm is proposed with superior competence to solve engineering problems. The proposed algorithm is substantiated hypothetically by using a paired t-test.

Keywords

Citation

Das, S., Sahu, T.P. and Janghel, R.R. (2021), "PSO-based group-oriented crow search algorithm (PGCSA)", Engineering Computations, Vol. 38 No. 2, pp. 545-571. https://doi.org/10.1108/EC-07-2019-0305

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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