Better algorithms for discrete optimization, with applications

更好的离散优化算法及其应用

• 批准号: 46602-2010
• 负责人: McCormick, SThomas
• 金额: $ 1.75万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=521799
• 关键词: Better; algorithms; discrete; optimization; applications

Many important business activities can usefully be represented as optimization models where we want to find the best possible feasible values of some decision variables that maximize or minimize some objective function. A challenging but important subset of these models require that the decision variables take only integer values. Such "discrete optimization" problems are provably hard in general, but there are many special cases where it can be proved that a fairly simple model has guaranteed integer optimal solutions.

许多重要的业务活动可以有效地表示为优化模型，我们希望找到一些决策变量的最佳可行值，最大化或最小化某些目标函数。这些模型的一个具有挑战性但重要的子集要求决策变量仅取整数值。这样的“离散优化”问题一般来说是很难证明的，但也有许多特殊情况，可以证明一个相当简单的模型有保证整数最优解。