Applying Methods from Combinatorial Optimization in Solving Real World Problems

应用组合优化方法解决现实问题

• 批准号: 36740-2007
• 负责人: Boyd, Sylvia
• 金额: $ 1.46万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=503371
• 关键词: Applying; Methods; Combinatorial; Optimization; Solving

Many practically important problems are combinatorial in nature. Some examples of such problems include the design of reliable communication networks, fast printed circuit board production, scheduling problems and routing problems. Many such problems are known to belong to a class called "NP-hard", which is strong evidence that these problems are extremely difficult to solve, and that it is unlikely that efficient techniques for finding the optimal (i.e. the best) solution exist. The lack of efficient methods for such problems is of real importance as there exist large scale, real world instances requiring solutions. Fortunately, in practice, it is often satisfactory to obtain solutions for these problems which, if not optimal, are at least guaranteed to lie within a certain satisfactory percentage of the optimal solution.

许多实际重要的问题本质上都是组合问题。 此类问题的一些示例包括可靠通信网络的设计、快速印刷电路板生产、调度问题和路由问题。 已知许多此类问题属于称为“NP-hard”的类别，这有力地证明了这些问题极难解决，并且不太可能存在找到最佳（即最佳）解决方案的有效技术。 缺乏解决此类问题的有效方法非常重要，因为存在需要解决方案的大规模现实世界实例。 幸运的是，在实践中，获得这些问题的解决方案通常是令人满意的，这些解决方案即使不是最佳的，也至少保证位于最佳解决方案的某个令人满意的百分比内。