期刊
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
卷 115, 期 3, 页码 549-570出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1023/A:1021251113462
关键词
no-free-lunch theorem; optimization; learning; decision making; search; strategy selection; impossibility theorem; representation and encoding; robustness; sensitivity; complexity
The no-free-lunch theorem of optimization (NFLT) is an impossibility theorem telling us that a general-purpose, universal optimization strategy is impossible. The only way one strategy can outperform another is if it is specialized to the structure of the specific problem under consideration. Since optimization is a central human activity, an appreciation of the NFLT and its consequences is essential. In this paper, we present a framework for conceptualizing optimization that leads to a simple but rigorous explanation of the NFLT and its implications(4).
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