期刊
COMPUTERS & OPERATIONS RESEARCH
卷 55, 期 -, 页码 1-11出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2014.10.008
关键词
Optimization; Metaheuristic method; Water wave optimization (WWO); Wave-current-bottom interactions; High-speed train scheduling
类别
资金
- National Natural Science Foundation of China [61020106009, 61105073, 61473263]
Nature-inspired computing has been a hot topic in scientific and engineering fields in recent years. Inspired by the shallow water wave theory, the paper presents a novel metaheuristic method, named water wave optimization (WINO), for global optimization problems. We show how the beautiful phenomena of water waves, such as propagation, refraction, and breaking, can be used to derive effective mechanisms for searching in a high-dimensional solution space. In general, the algorithmic framework of WWO is simple, and easy to implement with a small-size population and only a few control parameters. We have tested WWO on a diverse set of benchmark problems, and applied WINO to a real-world high-speed train scheduling problem in China. The computational results demonstrate that WWO is very competitive with state-of-the-art evolutionary algorithms including invasive weed optimization (IWO), biogeography-based optimization (BBO), bat algorithm (BA), etc. The new metaheuristic is expected to have wide applications in real-world engineering optimization problems. (C) 2014 The Author. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-SA license.
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