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: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=390206
• 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.

许多实际上重要的问题在本质上是组合的。 这些问题的一些例子包括可靠的通信网络的设计，快速印刷电路板生产，调度问题和路由问题。 已知许多这样的问题属于称为“NP难”的类别，这是这些问题极难解决的有力证据，并且不太可能存在用于找到最优（即最佳）解决方案的有效技术。 由于存在需要解决方案的大规模、真实的世界实例，因此缺乏针对此类问题的有效方法是真实的重要的。 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，如果不是最佳的，至少保证位于最佳解决方案的某个满意百分比内。