Constraint Solving and Programming: What Next?

In this paper we advocate for more flexible and user-friendly constraint solving environments, as well as for constraint programming languages which have great expressive power while maintaining a formal semantics based on few crucial concepts. We cite some of our work in these directions and we hint at subjects of our future research.     

Constraint Logic Programming and Integer Programming approaches and their collaboration in solving an assignment scheduling problem

Generalised Assignment Problems (GAP), traditionally solved by Integer Programming techniques, are addressed in the light of current Constraint Programming methods. A scheduling application from manufacturing, based on a modified GAP, is used to examine the performance of each technique under a variety of problem characteristics. Experimental evidence showed that, for a set of assignment problems, Constraint Logic Programming (CLP) performed consistently better than Integer Programming (IP). Analysis of the CLP and IP processes identified ways in which the search was effective. The insight gained from the analysis led to an Integer Programming approach with significantly improved performance. Finally, the issue of collaboration between the two contrasting approaches is examined with respect to ways in which the solvers can be combined in an effective manner.     

约束求解与优化技术的结合

提出了将混合约束问题转化为混合整数规划问题的方法.用约束求解方法及混合整数规划方法共同求解混合约束问题可以令二者相互借鉴,从而促进二者求解技术的进一步发展.同时,由混合约束问题转化而来的混合整数规划问题也可作为求解混合整数规划问题的测试问题（benchmarks）.     

Constraint Programming in Structural Bioinformatics

Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help analysing such data and eliciting new knowledge from it. In addition to string processing bioinformatics is often identified with machine learning used for mining the large banks of bio-data available in electronic format, namely in a number of web servers. Nevertheless, there are opportunities of applying other computational techniques in some bioinformatics applications. In this paper, we report the application of constraint programming to address two structural bioinformatics problems, protein structure prediction and protein interaction (docking). The efficient application of constraint programming requires innovative modelling of these problems, as well as the development of advanced propagation techniques (e.g. global reasoning and propagation), which were adopted in Chemera, a system that is currently used to support biochemists in their research.     

解约束规划问题的新型多目标粒子群优化算法

给出了一种求解约束规划问题的新解法。新方法将约束规划问题转化成两个目标优化问题,并对转化后的多目标优化问题设计了一种新型多目标粒子群优化算法(MOPSO)。数据实验表明该算法对带约束的规划问题求解是非常有效的。     

并发约束程序设计语言COPS及其执行模型

约束程序设计尤其是约束逻辑程序设计与并发约束程序设计在AI程序设计领域占据着越来越重要的位置。传统逻辑程序设计的基“计算即为定理证明”的计算风格虽获得了简洁优美的操作语义特性,但也付出了执行效率低的代价,当应用系统规模增大时,其性能严重下降以致崩溃。针对传统逻辑程序设计的这种可伸缩性问题,设计了一个基于并发约束程序设计概念的说明性语言COPS,旨在从语言设计与执行模型两方面降低说明性程序的不确定性,提高搜索与运行效率。在语言设计方面,通过引入确定性语言成分,避免不确定计算用于确定性目标所浪费的系统开销;在执行模型方面,在目标的并发穿叉执行与数据驱动的并发同步机制的基础上,实现“优先执行确定目标”策略与“最少假定”策略,作为约束传播的延伸,最大幅度地剪枝搜索空间,降低搜索复杂性。COPS提供的知识表示、推理与并发机制使其成为构造agent程序的理想语言。论文给出COPS语言的语法规范与执行模型的操作语义描述。     

约束编程与约束满足在产品装配中的应用

约束编程与约束满足问题是近三十年来在人工智能领域发展起来的一个研究方向。产品配置器近十几年来发展起来的一项技术。文中介绍约束编程及约束满足问题在按订单装配型产品配置器中的应用,并通过讨论说明了相对于传统配置方案求解过程,应用约束满足的优越性。     

Some Challenges for Constraint Programming

We propose a number of challenges for future constraint programming systems, including improvements in implementation technology (using global analysis based optimization and parallelism), debugging facilities, and the extension of the application domain to distributed, global programming. We also briefly discuss how we are exploring techniques to meet these challenges in the context of the development of the CIAO constraint logic programming system.     

基因表达式中含有等式约束的处理方法

基因表达式编程（Gene Expression Programming,GEP）算法是遗传家族的新成员,被广泛用于函数发现。在微分方程中,要寻找的函数需要满足初始值,即有时希望GEP找到的函数能够满足一些等式约束条件。提出了一种带拉格朗日插值函数的GEP,对生成的种群加入插值函数使其满足等式约束,为提高GEP算法的进化效率和精度对目标目标值加入尺度变化,对其放大或者缩小。这样缩短了GEP算法的进化距离,从而提高了种群的进化效率。通过仿真实例,结果表明该方法可行有效。     

可视化约束程序编程环境的设计与实现

该文提出了一种应用于多数化CAD系统的面向约束的程序设计思想,开发了一个实用的可视化约束程序编程环境。不仅简化了用户在参数化图形设计过程中大量约束程序的编程,而且提出了一种应用于参数化CAD系统设计图形约束程序的可视化方法。     

一种可扩展型CLP系统的统一建模方法

约束推理是人工智能中主要组成部分之一,可以解决实际优化调度和规划过程中的约束求解问题。这里在解释了约束逻辑程序设计的原理和过程基础上,打破封闭式约束逻辑程序设计系统,从软件工程上采用统一建模语言,提出一种新的开放的可扩展型约束逻辑程序设计结构系统。为实现可扩展的约束推理搜索系统,引进UML建模语言中用例图、类图和协作图。在建模基础上详细说明了可扩展约束逻辑程序设计中数学模型,搜索引擎和搜索驱动三者间的关系以及它们内部的工作内容。最后在描述系统结构后,提出了可扩展的内容。根据扩展因素,外界为满足更多的需要可扩展本系统的约束过滤器。     

基于雁群启示的粒子群优化算法的几何约束求解

几何约束是约束求解技术中最关键的问题之一.求解一个几何约束问题的最终目的是确定几何图形中每一个几何体的具体坐标位置.几何约束问题可以等价为求解非线性方程组问题.约束问题转化为一个优化问题.本文采用基于雁群启示的粒子群优化算法来求解该问题.该算法受雁群飞行特征启发,一方面将粒子排序,每个粒子跟随其前面那个较优粒子飞行,保持了多样性;另一方面使每个粒子利用更多其他粒子的有用信息,粒子之间的竞争被增强.两个方面的结合将平衡速度和精度之间的矛盾.实验表明,该方法可以提高几何约束求解的效率和收敛性.     

Executing Formal Specifications with Concurrent Constraint Programming

We have implemented a technique for execution of formal, model-based specifications. The specifications we can execute are written at a level of abstraction that is close to that used in nonexecutable specifications. The specification abstractions supported by our execution technique include using quantified assertions to directly construct post-state values, and indirect definitions of post-state values (definitions that do not use equality). Our approach is based on translating specifications to the concurrent constraint programming language AKL. While there are, of course, expressible assertions that are not executable, our technique is amenable to any formal specification language based on a finite number of intrinsic types and pre- and postcondition assertions.     

Modeling Biological Systems in Stochastic Concurrent Constraint Programming

We present an application of stochastic Concurrent Constraint Programming (sCCP) for modeling biological systems. We provide a library of sCCP processes that can be used to describe straightforwardly biological networks. In the meanwhile, we show that sCCP proves to be a general and extensible framework, allowing to describe a wide class of dynamical behaviours and kinetic laws.     

面向对象、泛型程序设计与类型约束检查

该文对面向对象和泛型程序设计(generic programming)的核心思想和方法进行了较为深入的分析．阐明了各自的目标、技术特征及其优缺点所在．介绍了泛型程序设计针对对象技术的不足所引进的重大革新,即通过类型需求抽象来设计通用、高效的数据结构和算法;着重论述了作者在进一步增强泛型程序设计实际运用方面所提出的改进工作．以C 语言的一个泛型编程扩充语言C**为实施例,详细说明了如何通过一种叫做“命名类型约束”的新的机制来比较完整地实现静态类型需求的直接语言支持和编译检查,为当前泛型程序设计模型的首例编程语言实例．     

A Comparative Study of Eight Constraint Programming Languages Over the Boolean and Finite Domains

This paper compares the efficiency of a number of Constraint Logic Programming (CLP) systems in the setting of finite domains as well as a specific aspect of their expressiveness (that concerning reification and meta-constraints). There are two key reasons for adopting CLP technology for solving a problem. The first is its expressiveness enabling a declarative solution with readable code which is vital for maintenance and the second is the provision of an efficient implementation for the computationally expensive procedures. However, CLP systems differ significantly both in how solutions may be expressed and the efficiency of their execution and it is important that both these factors are taken into account when choosing the best CLP system for a particular application. This paper aids this choice by illustrating differences between the systems, indicating their particular strengths and weaknesses.     

CLPGUI: A Generic Graphical User Interface for Constraint Logic Programming

CLPGUI is a generic graphical user interface for visualizing and controlling the execution of constraint logic programs. CLPGUI has been designed to be used in different contexts: initially for teaching purposes, then for debugging complex programs of real-world scale, and recently for developing end-user interfaces. The challenge of developing a tool which is generic w.r.t. both the constraint logic programming system and the visualizers, is addressed by a client-server architecture for connecting a CLP process to a Java-based GUI process, and by a non-intrusive tracing and control method based on annotations in the CLP program. Arbitrary constraints and goals can be posted incrementally from the GUI in an interactive manner, and arbitrary states can be recomputed. We describe several generic 2D and 3D viewers of the variables and of the search tree, and argue that the 3D representation is best-suited to apprehend the shape of large search trees. We also illustrate the use of CLPGUI for developing application-oriented end-user interfaces on two placement problems, one in virtual reality.     

Reasoning about Solids Using Constraint Logic Programming

The embedding of constraint satisfaction on the domain of discourse into a rule-based programming paradigm like logic programming provides a powerful reasoning tool. We present an application in spatial reasoning that uses this combination to produce a clear, concise, yet very expressive system through its ability to manipulate partial information. Three-dimensional solid objects in constructive solid geometry representation are manipulated, and their spatial relationship with one another, points, or regions is reasoned about. The language used to develop this application is QUAD-CLP(), an experimental constraint logic programming language of our own design, which is equipped with a solver for quadratic and linear arithmetic constraints over the reals.