期刊
SOFT COMPUTING
卷 19, 期 9, 页码 2587-2603出版社
SPRINGER
DOI: 10.1007/s00500-014-1424-4
关键词
Multi-objective optimization; Water cycle algorithm; Pareto-optimal solutions; Benchmark function; Metaheuristics
资金
- National Research Foundation of Korea (NRF) - Korean government (MSIP) [NRF-2013R1A2A1A01013886]
- National Research Foundation of Korea [2013R1A2A1A01013886] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据