Water cycle algorithm for solving multi-objective optimization problems

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

Research output: Contribution to journalArticlepeer-review

100 Citations (Scopus)


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
Issue number9
Publication statusPublished - 2015 Sept 17

Bibliographical 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:
© 2014, Springer-Verlag Berlin Heidelberg.


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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Geometry and Topology


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