Crocodile Hunting Strategy (CHS): A comparative study using benchmark functions

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Balavand A. R.

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Scientific Information Database

ISSN: 2588-4824

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF NUMERICAL ANALYSIS AND OPTIMIZATION Year:2022 | Volume:12 | Issue:2 Page(s): 397-425

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Information Journal Paper

Title

Crocodile Hunting Strategy (CHS): A comparative study using benchmark functions

Author(s)

Balavand A. R. | Issue Writer Certificate

Keywords

Crocodile hunting strategyQ4

Optimization algorithmsQ4

Numer-ical optimizationQ4

Classical benchmark functionsQ4

Constrained engineering design problemQ4

Abstract

The crocodiles have a good strategy for hunting the fishes in nature. These creatures are divided into two groups of chasers and ambushers when hunt-ing. The chasers direct prey toward shallow water with a powerful splash of its tail without catching them, and the ambushers wait in the shallow and try to snatch the fishes. Such behavior inspires the development of a new population-based optimization algorithm called the Crocodile hunting strategy (CHS). In order to verify the performance of the CHS, several Classical benchmark functions and four constrained engineering design op-timization problems are used. In the classical benchmark function, the comparisons are performed using ant colony optimization, differential evo-lution, genetic algorithm, and particle swarm optimization. Constrained engineering design problems are compared with firefly algorithm, harmony search, shuffled frog-leaping algorithm, and teaching-learning-based opti-mization. The results of the comparison show that different operators de-signed in the CHS algorithm lead to fast algorithm convergence and show better results compared to other algorithms.

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