Exploiting Structure in Satisfiability-Based Problem Solving

在基于可满足性的问题解决中利用结构

• 批准号: RGPIN-2015-05855
• 负责人: Mitchell, David
• 金额: $ 1.75万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=679720
• 关键词: Exploiting; Structure; Satisfiability; Based; Problem

Challenging combinatorial problems, including many optimization problems, arise in almost all areas of science, engineering and business, and applied computer science.  A particular approach to software for solving these problems, sometimes called satisfiability-based or constraint-based problem solving, provides workers facing such problems with a model-and-solve capability.  Users who are not experts in combinatorial problem solving need only describe their problem in a high-level, declarative, specification language to obtain solutions.  Technology based on this approach is very new, but is being shown highly effective for a growing range of problems.  This research aims to address two important limitations of the current technology.  One is that it is unknown how to adapt the solving algorithms at the core of this technology to exploit very high performance hardware which can be expected in the next decade, involving either very large numbers of compute cores and possibly adiabatic quantum annealing processors.  The second is that there is a wide range of problems for which the most effective algorithms are known as dynamic programming algorithms, but mode-and-solve technologies do not exploit this.  While of a different nature, both of these problems may be addressed in part by general methods which exploit particular structural properties of problem instances.  Taking advantage of these properties in practice, though, required new theory and algorithms, which are the subject of this project.

具有挑战性的组合问题，包括许多优化问题，几乎出现在科学、工程和商业的所有领域，并且应用计算机科学为工作人员提供了解决这些问题的特殊软件方法，有时称为基于可满足性或基于约束的问题解决。面对具有模型和解决能力的此类问题，非组合问题解决专家的用户只需使用高级的、声明性的规范语言来描述他们的问题即可获得解决方案。​这项研究旨在解决当前技术的两个重要局限性，一是尚不清楚如何调整该技术的核心解决算法来利用。未来十年预计会出现非常高性能的硬件，要么是大量的计算核心，要么可能涉及绝热量子退火处理器。第二个是，存在各种各样的问题，而最有效的算法被称为动态编程。算法，但模式和求解技术可以虽然性质不同，但这两个问题都可以通过利用问题实例的特定结构属性的通用方法来部分解决，但在实践中利用这些属性需要新的理论和算法。这个项目的主题。