Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation

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• 作者：Wenwen Li ; ^{psxwl8@nottingham.ac.uk} ; Ender Ö ; zcan ^{Ender.Ozcan@nottingham.ac.uk} ; Robert John ^{Robert.John@nottingham.ac.uk}
• 关键词：Wind farm ; Layout design ; Optimisation ; Hyper-heuristics ; Evolutionary algorithms ; Operation research
• 刊名：Renewable Energy
• 出版年：2017
• 出版时间：May 2017
• 年：2017
• 卷：105
• 期：Complete
• 页码：473-482
• 全文大小：1328 K
• 卷排序：105

文摘

Tested hyper-heuristics for multi-objective wind farm layout optimisation (WFLO). Hyper-heuristics control three multi-objective evolutionary algorithms (MOEAs). Hyper-heuristics perform better than each individual MOEA in the overall. Explored the trade-off between different objectives in WFLO.