分段线性拓扑、进化算法和优化问题
Piecewise Linear Topology, Evolutionary Algorithms, and Optimization Problems
摘要：
图式理论，马尔可夫链和统计力学已被用来解释进化算法（EA）的工作原理。所有这些方法都取得了逐步的成功，但每一种方法都受到与其非全球性观点有关的限制的阻碍。我们表明，移动到拓扑空间的调查，提高了我们的理解为什么EA的工作。
英文摘要：
Schemata theory, Markov chains, and statistical mechanics have been used to explain how evolutionary algorithms (EAs) work. Incremental success has been achieved with all of these methods, but each has been stymied by limitations related to its less-than-global view. We show that moving the investigation into topological space improves our understanding of why EAs work.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
