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

Iranian Journal of Numerical Analysis and Optimization

مقاله 8، دوره 12، شماره 2 - شماره پیاپی 22، آذر 2022، صفحه 397-425   

نوع مقاله: Research Article

شناسه دیجیتال (DOI): 10.22067/ijnao.2022.71418.1049

نویسنده

A. R. Balavand^*

Department of Industrial Engineering, Science and Research Branch, Islamic Azad University.

چکیده

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.

کلیدواژه‌ها

Crocodile hunting strategy؛ Optimization algorithms؛ Numer-ical optimization؛ Classical benchmark functions؛ Constrained engineering design problem

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