Mathematical Programming Techniques in Constraint Programming: A Short Overview

In recent years, the integration of techniques from Artificial Intelligence and Operations Research has shown to improve the solutions of complex and large scale combinatorial optimization problems, in terms of efficiency, scalability and optimality. In this context, Constraint Programming is an emerging discipline situated at the confluence of the two fields that has been recognized as a suitable environment for achieving such an integration. This paper briefly presents the integration directions explored in the literature, and provides some pointers to relevant work in these directions.     

Combining Constraint Programming and Linear Programming on an Example of Bus Driver Scheduling

This paper provides details of a successful application where the Column Generation algorithm was used to combine Constraint Programming and Linear Programming. In the past, constraint programming and linear programming were considered to be two competing technologies that solved similar types of problems. Both these technologies had their strengths and weaknesses. This paper shows that the two technologies can be combined together to extract the strengths of both these technologies. Details of a real-world application to optimize bus driver duties is given here. This system was developed by ILOG for a major software house in Japan using ILOG-Solver and ILOG-CPLEX, constraint programming and linear programming C/C++ libraries.     

Integrating Operations Research in Constraint Programming

This paper presents Constraint Programming as a natural formalism for modelling problems, and as a flexible platform for solving them. CP has a range of techniques for handling constraints including several forms of propagation and tailored algorithms for global constraints. It also allows linear programming to be combined with propagation and novel and varied search techniques which can be easily expressed in CP. The paper describes how CP can be used to exploit linear programming within different kinds of hybrid algorithm. In particular it can enhance techniques such as Lagrangian relaxation, Benders decomposition and column generation.     

较多约束规划及其最优性条件

本文研究了文[1]中提出的较多约束规划的基本问题，在给出问题的较多约束集结构表示的基础上，证明了这类问题的较多约束最优解要满足的Fritz John条件和Kuhn-Tucker条件。     

一类稀疏约束非线性规划的约束规格

研究一类带有闭凸集约束的稀疏约束非线性规划问题,这类问题在变量选择、模式识别、投资组合等领域具有广泛的应用.首先引进了限制性Slater约束规格的概念,证明了该约束规格强于限制性M-F约束规格,然后在此约束规格成立的条件下,分析了其局部最优解成立的充分和必要条件.最后,对约束集合的两种具体形式,指出限制性Slater约束规格必满足,并给出了一阶必要性条件的具体表达形式.     

Soft Constraint Logic Programming and Generalized Shortest Path Problems

In this paper we study the relationship between Constraint Programming (CP) and Shortest Path (SP) problems. In particular, we show that classical, multicriteria, partially ordered, and modality-based SP problems can be naturally modeled and solved within the Soft Constraint Logic Programming (SCLP) framework, where logic programming is coupled with soft constraints. In this way we provide this large class of SP problems with a high-level and declarative linguistic support whose semantics takes care of both finding the cost of the shortest path(s) and also of actually finding the path(s). On the other hand, some efficient algorithms for certain classes of SP problems can be exploited to provide some classes of SCLP programs with an efficient way to compute their semantics.     

适应编程需要的一种动态规划模型解法

由计算机软件编程需要出发,对库存管理中的一种动态规划方法进行了讨论,推导出了统一规范表达的允许状态集合和允许决策集合,并由此给出了计算程序框图,为计算机处理类似问题提供了依据。     

基于时间约束的生产过程优化问题研究

本文提出一个实际的生产过程优化问题:基于时间约束的生产过程优化问题。客户要求企业在规定时间内完成指定批量工件的生产任务,该问题便是从中引出的。该问题的目标是在满足生产时间的条件下最小化总生产成本。本文为该问题建立了整数规划模型。然后以某厂工作缸生产过程为例,采用数学规划软件Cplex 9.0求解模型。     

运筹学中的转化思想

本通过转化思想，给出运筹学中各分支间的关联与统归。     

运筹学课程教学中的探索与实践

结合教学实践经验,从提高学生的兴趣和积极性出发,在运筹学课程的教学过程中,提出了以学生为本,改进教学内容和教学方法,并把数学建模的思想融到运筹学课程的教学中去,从而提高学生的学习效果和教师的教学效果.     

Cane Railway Scheduling via Constraint Logic Programming: Labelling Order and Constraints in a Real-Life Application

In Australia, cane transport is the largest unit cost in the manufacturing of raw sugar, making up around 35% of the total manufacturing costs. Producing efficient schedules for the cane railways can result in significant cost savings. This paper presents a study using Constraint Logic Programming (CLP) to solve the cane transport scheduling problem. Tailored heuristic labelling order and constraints strategies are proposed and encouraging results of application to several test problems and one real-life case are presented. The preliminary results demonstrate that CLP can be used as an effective tool for solving the cane transport scheduling problem, with a potential decrease in development costs of the scheduling system. It can also be used as an efficient tool for rescheduling tasks which the existing cane transport scheduling system cannot perform well.     

排序问题的线性规划松弛方法

本文研究排序问题的线性规划松弛方法，对单台机器排序问题1｜prec｜∑wjCj介绍基于三个确定性线性规划松弛的2一近似算法，对平行机排序问题R｜rij｜（wjCj）介绍基于随机线性规划松弛的2-近似算法。这后一个算法对排序问题R｜（wjCj｜是3／2-近似算法．     

运筹学是什么

指出运筹学是一种探索最优化的文化.     

运筹学中若干离散规划问题的相对差分搜索解法

运筹学中有很多离散规划问题。其中的线性规划通常用分枝定界法或割平面法，还有图上作业法求解。不论哪种方法工作量都不小，而且效率低；至于非线性规划大都是用动态规划法求解，也很麻烦、耗时。对于大规模问题，不论线性或非线性离散规划，现有解法都受到问题规模的限制；还有资源分配和背包问题至今没有见到解决方法。本文就是为了解决这些问题，提出了相对差分搜索算法。通过5个算例和其它文献中的一些算例计算验证了本法简单、快速、有效和精确，尤其不受问题规模的限制是其最大的优点。     

运筹学中涉及多学科的一个案例

讨论了运筹学中的一个案例,在不同条件下,它涉及不同的运筹学分支以及经济学、社会学等领域。因此,教材中如能包含若干个这种例子,对引导学生多学科、全方位思考问题将是大有裨益的。     

线性约束凸规划的鞍梯度法

求线性约束凸规划问题的最优解。方法：在鞍梯度法的基础上提出了一个具有全局收敛性的原一对偶外点算法。结果：每步迭代利用Lagrange函数的鞍梯度构造搜索方向，生成次可行解序列，由此得到的序列的极限就是原-对偶问题的最优解。结论：即使从原一对偶问题的不可行点开始迭代算法也收敛。     

线性规划对偶问题的一个注记

指出了线性规划对偶问题定义中的一个小漏洞,并作了改正     

带有约束线性分式规划问题的最优性条件

In this article,the authors discuss the optimal conditions of the linear fractional programming problem and prove that a locally optional solution is a globally optional so- lution and the locally optimal solution can be attained at a basic feasible solution with constraint condition.     

一种改进的进化规划算法

本对于全局优化问题提出一个改进的进化规划算法，该算法以概率p接收基于电磁理论求出合力方向作为随机搜索方向，以概率1-p接收按正态分布产生的随机搜索方向。改进算法不仅克服了传统进化规划算法随机搜索的盲目性，而且保留了传统进化规划算法全局搜索性。本算法应用于几个典型例题，数值结果表明本算法是可行的，有效的。     

1996~2017年《Operations Research》期刊发文统计分析

《Operations Research》(OR)是运筹与管理科学领域的顶级期刊,对其刊文进行统计分析,剖析国际运筹学科领域的主流研究机构及合作影响,探究当前研究热点问题及学科发展趋势,对于促进我国运筹学科领域的发展具有十分重要的指引作用.基于对WOS核心数据库中该期刊1996至2017年间全部刊文的统计分析,得出以下结论:近年来我国学者发文量稳步提升,表明我国运筹学科领域研究水平的显著提高,但其影响力仍有待进一步提升;机构合作、国际合作都有助于文章引文量的提升;引证分析显示柔性制造(流程柔性及效率)、巢式Logit模型的应用、网络收益管理等7个研究方向是当前、并继续成为运筹领域的研究热点.