Linear programming software tools on UNIX System

Linear programming(LP) is one of the most widely used Operations Research/Management Science/Industrial Engineering techniques. Recently, multiple criteria decision making or multiple objective linear programming has been well established as a practical approach to seeking satisfactory solutions to real-world decision problems.

In this paper we develop software tools for solving various linear programming problems such as a traditional LP problem, bicriteria LP problem, and multi-criteria LP problem on UNIX system. In a phase for reading data of various LP problems, we define a BNF(Backus-Nauel form) of various LP problems and implement BNF rules by using the C programming language.

In a phase for computing various LP problems, we use efficient methods for solving LP problems, develop various software tools on UNIX system, and combine each LP tool corresponding to an user request in which the Shell programming is used.

We also demonstrate some real-world LP problems by using LP software tools developed here on an UNIX System. Sanyo MPS 020.     

Dynamic programming equations for discounted constrained stochastic control

In this paper, the application of the dynamic programming approach to constrained stochastic control problems with expected value constraints is demonstrated. Specifically, two such problems are analyzed using this approach. The problems analyzed are the problem of minimizing a discounted cost infinite horizon expectation objective subject to an identically structured constraint, and the problem of minimizing a discounted cost infinite horizon minimax objective subject to a discounted expectation constraint. Using the dynamic programming approach, optimality equations, which are the chief contribution of this paper, are obtained for these problems. In particular, the dynamic programming operators for problems with expectation constraints differ significantly from those of standard dynamic programming and problems with worst-case constraints. For the discounted cost infinite horizon cases, existence and uniqueness of solutions to the dynamic programming equations are explicitly shown by using the Banach fixed point theorem to show that the corresponding dynamic programming operators are contractions. The theory developed is illustrated by numerically solving the constrained stochastic control dynamic programming equations derived for simple example problems. The example problems are based on a two-state Markov model that represents an error prone system that is to be maintained.     

基于模拟退火算法的遗传程序设计方法

遗传程序设计（GP）是运用遗传算法的思想，通过生成计算机程序来解决问题的，但用它来解决大型或复杂问题时，就存在一些难以解决的问题，尤其是大量使用计算机内存和CPU时间，大大影响了工作性能。以符号回归问题为例，针对传统的遗传程序设计方法在解决问题时所遇到的困难，提出一个基于模拟退火算法的遗传程序设计方法，进一步提高GP系统求解问题的能力。     

Applications of mathematical models: An expert system for selecting solution methods for solving nonlinear programming problems

This paper presents an expert system for selecting solution methods for solving nonlinear programming problems. No general method exists for solving nonlinear programming problems in the same manner as the Simplex algorithm solves linear programming problems. Hence to some extent nonlinear programming even today exists as an experimental field of research. It has advanced to this date through the proposal and programming of particular algorithms, examinations of the results of the implementation of the algorithms to problems of interest, and the construction of better algorithms based on the experience gained. Computational experiences of many numerical methods such as direct search methods, method of multipliers, and linear approximation methods have been widely reported in literature int he past two decades. However, there is no unified approach to solve a genral NLP problem.

A small scale expert system has been developed using the Texas Instruments Personal Consultant Plus (PCPLUS) software to provide an organised approach for solving NLP problems. A knowledge base has been constructed to represent the past computational experiences of different solution methods on different classes of NLP problems. The system can be effectively used in conjunction with OPTLIB (1), which is a optimization program library for solving NLP problems. The purpose of the system is to guide inexperienced engineers to choose a proper NLP solution method and to serve as teaching aid. In selecting the methods more stress has been laid on the sure-footedness of the method, than on computational time and storage space requirement to make it more reliable for users. This paper presents the knowledge organisation, rules and the testing results.     

A high-performance neural network for solving linear and quadraticprogramming problems

Two classes of high-performance neural networks for solving linear and quadratic programming problems are given. We prove that the new system converges globally to the solutions of the linear and quadratic programming problems. In a neural network, network parameters are usually not specified. The proposed models can overcome numerical difficulty caused by neural networks with network parameters and obtain desired approximate solutions of the linear and quadratic programming problems.     

DISOPT—A general programme for continuous and discrete non-linear programming problems†

An integrated computer programme in Fortran IV for continuous or discrete non linear programming problems is presented. Several recent techniques and algorithms for non-linear programming have been adapted and new ideas have been introduced. They include the minimax and exterior-point approaches to non-linear programming, least pth optimization and the Dakin tree-search algorithm. The user may optionally choose the combination of techniques and algorithms best suited to his problems. Since many practical design problems can be easily formulated as non-linear programming problems, the programme, called DISOPT, enjoys a very wide range of applications such as continuous and discrete tolerance assignments, digital filter design, circuit design, system modelling and approximation problems. Numerical results for a number of functions and circuit tolerance optimization problems are presented in this paper to demonstrate the performance of DISOPT.     

Evolutionary Computation Techniques for Nonlinear Programming Problems

This paper presents several evolutionary computation techniques and discusses their applicability to nonlinear programming problems. On the basis of this presentation we discuss also a construction of a new hybrid optimization system, Genocop 11, and present its experimental results on a few test cases (nonlinear programming problems).     

VFP 中生成可执行文件的方法和技巧

针对当前VFP数据库编程中,多数编程者由于方法掌握不当,遇到的一些问题,本文首先对项目管理器做了简要分析,其次经过设计、编程、制作等系列工作,最后通过反复调试,制作出系统安装磁盘,编制完成了一个完整的可脱离VFP环境的应用系统,用户使用起来也非常方便。     

Bounds for convex variational programming problems arising in power system scheduling and control

The convex variational programming problem has been found of practical importance to power system scheduling and control. Convex variational programming problems are closely related to the convex programming problems treated by Kuhn and Tucker [8]. Among their positive attributes are the absence of difficulties with weak relative minima and with saddle-point or conjugate-point conditions. As a result it is feasible to develop dual-variational problems and to provide estimates for bracketing the extreme value of the functional of the variational problem when gradient or successive approximations methods are employed for determination of near optimal control schedules. This paper develops necessary and sufficient conditions for the optimal control schedule and a means for numerically determining bounds to the extreme value of the functional. Applications are given to the problem of hydrothermal power system coordination.     

A distributed system for learning programming on-line

Several Web-based on-line judges or on-line programming trainers have been developed in order to allow students to train their programming skills. However, their pedagogical functionalities in the learning of programming have not been clearly defined. EduJudge is a project which aims to integrate the “UVA On-line Judge”, an existing on-line programming trainer with an important number of problems and users, into an effective educational environment consisting of the e-learning platform Moodle and the competitive learning tool QUESTOURnament. The result is the EduJudge system which allows teachers to apply different pedagogical approaches using a proven e-learning platform, makes problems easy to search through an effective search engine, and provides an automated evaluation of the solutions submitted to these problems. The final objective is to provide new learning strategies to motivate students and present programming as an easy and attractive challenge. EduJudge has been tried and tested in three algorithms and programming courses in three different Engineering degrees. The students’ motivation and satisfaction levels were analysed alongside the effects of the EduJudge system on students’ academic outcomes. Results indicate that both students and teachers found that among other multiple benefits the EduJudge system facilitates the learning process. Furthermore, the experiment also showed an improvement in students’ academic outcomes. It must be noted that the students’ level of satisfaction did not depend on their computer skills or their gender.     

基于B/S架构的多用户在线程序评判系统设计与实现

针对现有在线程序评判系统存在的判题效率和安全性问题,本文在分析多用户在线评判系统的功能需求基础上,提出了一种基于B/S架构采用Struts+Spring+Hibernate(SSH)组合框架的多用户在线程序评判系统,介绍了系统的程序评判原理及采用的安全机制。该系统不但可以用于ACM程序设计等比赛,而且可以为程序设计课程教学提供很好的辅助实验平台支持。     

基于Hopfield神经网络的双线性离散系统最优控制

将基于二次型性能指标的离散双线性系统最优控制问题转化为动态规划问题，并用Hopfield神经网络（HNN）求解．该方法具有结构简单、易于硬件实现、求解速度快且能求得精确最优解等特点．在复杂系统的实时优化与控制等方面具有广阔的应用前景．     

基于fisheye views算法解决可视化程序设计语言问题的研究

可视化程序设计语言已经引起了越来越多学者的研究兴趣,并产生了一系列研究成果。在对编程元素由二维图形对象构成的传统可视化程序设计语言中产生的两个显示问题进行了详细分析,提出引入一种改进的fisheye views算法来解决这些问题的方法。并通过设计的原型系统VPMF表征了该方法的效果和可行性。     

面向任务协同程序设计的研究

针对软件系统呈现出的新的自然特性,面向对象程序设计与面向方面程序设计不能提供很好的技术支撑。文章提出面向任务协同程序设计,对其思想和实现原理进行了阐述,并对其解决的问题与意义做了简述。     

VB与VC混合编程技术的研究

VB具有快速实现系统顶层功能的优点,而VC能很好地完成底层操作.介绍如何结合这两种语言的优点进行混合编程的几种方法,通过具体实例演示它们的应用.并且对混合编程中需要注意的问题也进行了阐述.     

面向方面的信息系统建模方法及应用研究

随着面向对象软件开发技术的不断发展以及软件规模的不断扩大,系统地分析和设计变得日益复杂。软件开发过程中很难利用现有的编程技术（如面向对象编程、面向过程编程）对横切系统多个模块的关注点进行鉴别、理解和模块化。为解决面向对象开发方法中的耦合性较高、可重用性较低和代码分散等问题,将面向方面的编程思想引人到系统分析和设计阶段,提出了一种面向方面的信息系统建模方法。     

Application of mathematical programming in the design of optimal control systems†

The problem of applying the various computational methods of mathematical programming in the design of an optimal control system is discussed. A general case of non-linear, non-autonomous, state equations, subject to inequality constraints on both state and control variables, is considered. Both continuous and discrete time systems are investigated. In case of discrete time systems, the sampling intervals are assumed generally unequal and aperiodic, with inequality constraints imposed upon them.

Systems like these impose considerable computational difficulties when treated by the maximum principle or dynamie programming. Using mathematical programming, one may simplify a wide class of those computational problems.

Several examples of applying mathematical programming to particular control problems are presented.     

The methodology of multiple-criteria decision making in the optimization of an urban transportation system: case study of Poznań City in Poland

The methodology of multiple-criteria decision making applied to the optimization of an urban transportation system is presented in the paper. Three mathematical models of different complexity are constructed to optimize the allocation of vehicles to certain routes in a mass transit system. All models take into account both passengers' and operator's objectives. The optimization problems are formulated in terms of multiple-objective fuzzy linear programming and multiple-objective non-linear programming. The sensitivity and precision analysis of the models is carried out. Two interactive multi-objective mathematical programming procedures are utilized to solve the problems. They generate samples of Pareto-optimal compromise solutions and provide the decision maker (DM)with an effective tool that supports him/her in the decision making process. Finally, the DM selects the solution that best fits his or her expectations.     

Scalability of hybrid programming for a CFD code on the Earth Simulator

The Earth Simulator (ES) is an SMP cluster system. There are two types of parallel programming models available on the ES. One is a flat programming model, in which a parallel program is implemented by MPI interfaces only, both within an SMP node and among nodes. The other is a hybrid programming model, in which a parallel program is written by using thread programming within an SMP node and MPI programming among nodes simultaneously. It is generally known that it is difficult to obtain the same high level of performance using the hybrid programming model as can be achieved with the flat programming model.

In this paper, we have evaluated scalability of the code for direct numerical simulation of the Navier–Stokes equations on the ES. The hybrid programming model achieves the sustained performance of 346.9 Gflop/s, while the flat programming model achieves 296.4 Gflop/s with 16 PNs of the ES for a DNS problem size of 256³. For small scale problems, however, the hybrid programming model is not as efficient because of microtasking overhead. It is shown that there is an advantage for the hybrid programming model on the ES for the larger size problems.