Applications and Efficient Execution of Constraint Logic Programming Over a Real-Number Domain

约束逻辑编程（CLP）是建立在谓词演算基础上的一系列编程语言，具有基于约束的问题表示的附加表达性。家族中的每种语言都是通过程序变量的值域来区分的。Prolog是这个家族中最著名的语言，可以看作是无限树域的CLP。本文主要研究实数域（CLP(R)）上的CLP。CLP(R)的实现通常将约束限制为线性方程和不等式，并且由此产生的语言已被证明足以表达各种调度，仓库定位，削减库存，期权交易和人员名单问题，以及AI谜题。然而，CLP(R)的实用性受到大多数问题所需的大搜索空间和约束满足算法的复杂性的限制。更简单地说，并非总能从CLP的表达性中获益，因为许多有用的问题需要很长时间才能解决。本研究的目标是确定CLP(R)应用程序，如果执行速度可以加快，将是可行的，并找到通过更有效的约束满足算法减少执行时间的方法。＊＊＊

9619523 Constraint logic programming (CLP) is a family of programming languages built upon predicate calculus, with the added expressiveness of constraint-based problem representations. Each language in the family is distinguished by the domain of values for the program variables. Prolog is the best-known language in the family and can be viewed as CLP in the domain of infinite trees. This research focuses on CLP over a real-number domain (CLP(R)). Implementations of CLP(R) generally restrict constraints to linear equations and inequalities, and the resulting languages have proven expressive enough for a variety of scheduling, warehouse location, cutting stock, options trading, and crew rostering problems, as well as AI puzzles. However, CLP(R)'s usefulness is limited by the large search space required for most problems and by the complexity of the constraint satisfaction algorithm. Stated more simply, it is not always possible to benefit from CLP's expressiveness, since many useful problems take too long to solve. The goal of this research is to identify CLP(R) applications that would be feasible if execution could be sped up, and to find ways to cut down on execution time through a more efficient constraint satisfaction algorithm. ***