Water cycle algorithm for solving constrained multi-objective optimization problems

Ali Sadollah; Hadi Eskandar; Joong Hoon Kim

doi:10.1016/j.asoc.2014.10.042

Water cycle algorithm for solving constrained multi-objective optimization problems

Ali Sadollah, Hadi Eskandar, Joong Hoon Kim

School of Civil, Environmental and Architectural Engineering

Research output: Contribution to journal › Article

115 Citations (Scopus)

Abstract

In this paper, a metaheuristic optimizer, the multi-objective water cycle algorithm (MOWCA), is presented for solving constrained multi-objective problems. The MOWCA is based on emulation of the water cycle process in nature. In this study, a set of non-dominated solutions obtained by the proposed algorithm is kept in an archive to be used to display the exploratory capability of the MOWCA as compared to other efficient methods in the literature. Moreover, to make a comprehensive assessment about the robustness and efficiency of the proposed algorithm, the obtained optimization results are also compared with other widely used optimizers for constrained and engineering design problems. The comparisons are carried out using tabular, descriptive, and graphical presentations.

Original language	English
Pages (from-to)	279-298
Number of pages	20
Journal	Applied Soft Computing Journal
Volume	27
DOIs	https://doi.org/10.1016/j.asoc.2014.10.042
Publication status	Published - 2014

Keywords

Benchmark function
Constrained optimization
Metaheuristics
Multi-objective optimization
Pareto optimal solutions
Water cycle algorithm

ASJC Scopus subject areas

Software

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Sadollah, A., Eskandar, H., & Kim, J. H. (2014). Water cycle algorithm for solving constrained multi-objective optimization problems. Applied Soft Computing Journal, 27, 279-298. https://doi.org/10.1016/j.asoc.2014.10.042

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