Water cycle algorithm for solving multi-objective optimization problems

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

Research output: Contribution to journalArticle

57 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 languageEnglish
Pages (from-to)2587-2603
Number of pages17
JournalSoft Computing
Volume19
Issue number9
DOIs
Publication statusPublished - 2015 Sep 17

Keywords

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

ASJC Scopus subject areas

  • Software
  • Geometry and Topology
  • Theoretical Computer Science

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