CWCA: Complex-valued encoding water cycle algorithm

Guo Zhou; Yongquan Zhou; Zhonghua Tang; Qifang Luo; Guo Zhou; Yongquan Zhou; Zhonghua Tang; Qifang Luo

doi:10.3934/mbe.2021294

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 5: 5836-5864. doi: 10.3934/mbe.2021294

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Research article Special Issues

CWCA: Complex-valued encoding water cycle algorithm

1.
Department of Science and Technology Teaching, China University of Political Science and Law, Beijing 100088, China
2.
College of Artificial Intelligence, Guangxi University for Nationalities, Nanning 530006, China
3.
Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis, Nanning 530006, China

Received: 25 April 2021 Accepted: 22 June 2021 Published: 29 June 2021

Since the meta-heuristic water cycle algorithm (WCA) was presented, it has been used extensively in scientific computation and engineering optimization. The aims of this study are to improve the exploration and exploitation capabilities of the WCA algorithm, accelerate its convergence speed, and enhance its calculation accuracy. In this paper, a novel complex-valued encoding WCA (CWCA) is proposed. The positions of rivers and streams are divided into two parts, that is, the real part and imaginary part, and modified formulas for the new positions of rivers and streams are proposed. To evaluate the performance of the CWCA, 12 benchmark functions and four engineering examples were considered. The experimental results indicated that the CWCA had higher precision and convergence speed than the real-valued WCA and other well-known meta-heuristic algorithms.
- water cycle algorithm,
- complex-valued water cycle algorithm,
- benchmark functions,
- engineering optimization,
- meta-heuristic optimization
Citation: Guo Zhou, Yongquan Zhou, Zhonghua Tang, Qifang Luo. CWCA: Complex-valued encoding water cycle algorithm[J]. Mathematical Biosciences and Engineering, 2021, 18(5): 5836-5864. doi: 10.3934/mbe.2021294

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Abstract

Since the meta-heuristic water cycle algorithm (WCA) was presented, it has been used extensively in scientific computation and engineering optimization. The aims of this study are to improve the exploration and exploitation capabilities of the WCA algorithm, accelerate its convergence speed, and enhance its calculation accuracy. In this paper, a novel complex-valued encoding WCA (CWCA) is proposed. The positions of rivers and streams are divided into two parts, that is, the real part and imaginary part, and modified formulas for the new positions of rivers and streams are proposed. To evaluate the performance of the CWCA, 12 benchmark functions and four engineering examples were considered. The experimental results indicated that the CWCA had higher precision and convergence speed than the real-valued WCA and other well-known meta-heuristic algorithms.

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