Water cycle algorithm for solving multi-objective optimization problems

Ali Sadollah; Hadi Eskandar; Ardeshir Bahreininejad; Joong Hoon Kim

doi:10.1007/s00500-014-1424-4

Water cycle algorithm for solving multi-objective optimization problems

Ali Sadollah, Hadi Eskandar, Ardeshir Bahreininejad, Joong Hoon Kim

School of Civil, Environmental and Architectural Engineering

Research output: Contribution to journal › Article › peer-review

90 Citations (Scopus)

Abstract

In this paper, the water cycle algorithm (WCA), a recently developed metaheuristic method is proposed for solving multi-objective optimization problems (MOPs). The fundamental concept of the WCA is inspired by the observation of water cycle process, and movement of rivers and streams to the sea in the real world. Several benchmark functions have been used to evaluate the performance of the WCA optimizer for the MOPs. The obtained optimization results based on the considered test functions and comparisons with other well-known methods illustrate and clarify the robustness and efficiency of the WCA and its exploratory capability for solving the MOPs.

Original language	English
Pages (from-to)	2587-2603
Number of pages	17
Journal	Soft Computing
Volume	19
Issue number	9
DOIs	https://doi.org/10.1007/s00500-014-1424-4
Publication status	Published - 2015 Sep 17

Keywords

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

ASJC Scopus subject areas

Theoretical Computer Science
Software
Geometry and Topology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s00500-014-1424-4

Cite this

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title = "Water cycle algorithm for solving multi-objective optimization problems",

abstract = "In this paper, the water cycle algorithm (WCA), a recently developed metaheuristic method is proposed for solving multi-objective optimization problems (MOPs). The fundamental concept of the WCA is inspired by the observation of water cycle process, and movement of rivers and streams to the sea in the real world. Several benchmark functions have been used to evaluate the performance of the WCA optimizer for the MOPs. The obtained optimization results based on the considered test functions and comparisons with other well-known methods illustrate and clarify the robustness and efficiency of the WCA and its exploratory capability for solving the MOPs.",

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note = "Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2013R1A2A1A01013886). Publisher Copyright: {\textcopyright} 2014, Springer-Verlag Berlin Heidelberg.",

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AU - Sadollah, Ali

AU - Eskandar, Hadi

AU - Bahreininejad, Ardeshir

AU - Kim, Joong Hoon

N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2013R1A2A1A01013886). Publisher Copyright: © 2014, Springer-Verlag Berlin Heidelberg.

PY - 2015/9/17

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N2 - In this paper, the water cycle algorithm (WCA), a recently developed metaheuristic method is proposed for solving multi-objective optimization problems (MOPs). The fundamental concept of the WCA is inspired by the observation of water cycle process, and movement of rivers and streams to the sea in the real world. Several benchmark functions have been used to evaluate the performance of the WCA optimizer for the MOPs. The obtained optimization results based on the considered test functions and comparisons with other well-known methods illustrate and clarify the robustness and efficiency of the WCA and its exploratory capability for solving the MOPs.

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KW - Metaheuristics

KW - Multi-objective optimization

KW - Pareto-optimal solutions

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Water cycle algorithm for solving multi-objective optimization problems

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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