Scalable computation of high-order optimization queries
Scalable computation of high-order optimization queries
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DOI：
10.1145/3299881
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发表时间：
2019-01
影响因子：
22.7
通讯作者：
Matteo Brucato;A. Abouzeid;A. Meliou
中科院分区：
文献类型：
--
作者：
Matteo Brucato;A. Abouzeid;A. Meliou
约束优化问题是金融、交通、制造和医疗等领域重要应用的核心问题。建模和解决这些问题一直依赖于特定于应用程序的解决方案，这些解决方案通常很复杂、容易出错，而且不能泛化。我们的目标是创建一种独立于域的声明性方法，由与这些问题相关的数据通常所在的系统(即数据库)支持和支持。我们提出了一个支持包查询的完整系统，这是一种新的查询模型，它扩展了传统的数据库查询来处理复杂的约束和对答案集的偏好，允许在数据库中对一类重要的约束优化问题-整数线性规划(ILP)--进行声明性说明和有效评估。
Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. We present a complete system that supports package queries, a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets, allowing the declarative specification and efficient evaluation of a significant class of constrained optimization problems---integer linear programs (ILP)---within a database.