Improved Mathematical Programming Techniques for Approximation Algorithms

改进近似算法的数学编程技术

• 批准号: RGPIN-2015-06496
• 负责人: Friggstad, Zachary
• 金额: $ 1.68万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=591096
• 关键词: Improved; Mathematical; Programming; Techniques; Approximation

A striking number of problems in discrete optimization are, unfortunately, computationally intractable. These problems stem from issues faced by our complex society: coordinating vehicles in a transportation network, compiling code to create efficient executable programs, determining placements of fire or ambulance stations to improve response time. More precisely, many such problems are NP-hard meaning we do not have, nor do we expect, any efficient algorithms to solve these problems optimally. To cope with this difficulty, we focus on devising efficient algorithms that find near-optimum solutions.

不幸的是，离散优化中的许多问题在计算上都很难处理。这些问题源于我们复杂的社会所面临的问题：协调交通网络中的车辆，编译代码以创建高效的可执行程序，确定消防站或救护车的位置以改善响应时间。更准确地说，许多这样的问题是NP难的，这意味着我们没有任何有效的算法来最优地解决这些问题，也不希望有任何有效的算法来优化解决这些问题。为了应对这一困难，我们专注于设计找到近最优解的高效算法。