首页> 外文会议>Annual symposium on theoretical aspects of computer science >Evolutionary Algorithms and the Maximum Matching Problem
【24h】

Evolutionary Algorithms and the Maximum Matching Problem

机译:进化算法和最大匹配问题

获取原文

摘要

Randomized search heuristics like evolutionary algorithms are mostly applied to problems whose structure is not completely known but also to combinatorial optimization problems. Practitioners report surprising successes but almost no results with theoretically well-founded analyses exist. Such an analysis is started in this paper for a fundamental evolutionary algorithm and the well-known maximum matching problem. It is proven that the evolutionary algorithm is a polynomial-time randomized approximation scheme (PRAS) for this optimization problem, although the algorithm does not employ the idea of augmenting paths. Moreover, for very simple graphs it is proved that the expected optimization time of the algorithm is polynomially bounded and bipartite graphs are constructed where this time grows exponentially.
机译:随机搜索启发式等渐变算法大多应用于结构不完全已知的问题,而且是组合优化问题的问题。从业者举报了令人惊讶的成功,但在理论上,几乎没有结果存在良好的分析。在本文中开始这种分析,用于基本的进化算法和众所周知的最大匹配问题。据证正,进化算法是该优化问题的多项式随机近似方案(PRA),尽管算法不采用增强路径的想法。此外,对于非常简单的曲线图,证明了算法的预期优化时间是多项有界的,并且在这次呈指数增长的情况下构造二分图。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号