空间桁架结构拓扑优化设计的线性规划方法

本文以杆件内力为设计变量,构造了多工况作用下空间桁架结构拓扑优化的线性规划模型,考虑了应力和位移约束,能够避免奇异最优拓扑和不稳定结构的产生。     

关于布尔函数的二次逼近

本文首先利用矩阵形式引入了二阶ｗａｌｓｈ谱的概念并讨论了其性质，其次引入了二次ｂｅｎｔ函数的概念，同时论述了二次ｂｅｎｔ函数的密码学意义。     

A load dispatch method using fractional programming and semidefinite programming

This paper describes a load dispatch method which minimizes power cost—[fuel cost]/[electric output]—for a power system with thermal plants and energy storage facilities. The proposed method employs fractional programming to convert a minimization problem with fractional objective function to a series of quadratic minimization problems, and semidefinite programming to solve converted problems. The method provides the optimum time‐dependent power output/input and storage level of energy storage facilities as well as time‐dependent power output of thermal plants. The method has been applied to a power system with five thermal plants, two energy storage facilities of various performances, and five load demands. The optimum load scheme of four time mesh points is obtained for the thermal plants and energy storage facilities. The fractional programming successfully converges the optimal scheme through a few iterations. The semidefinite programming deals with a variable matrix of 164 dimensions, and 185 inequality constraints. © 2001 Scripta Technica, Electr Eng Jpn, 138(2): 49–58, 2002     

Solubility of amaranth seed proteins in sodium sulphate and sodium chloride: the main factor in quantitative extraction for analysis

Nitrogen was extracted more efficiently from amaranth seed with 0.04 M Na₂SO₄ (5% w/v) than with either 0.09 M or 0.17 M NaCl (5% or 10% w/v), despite both solutions having the same ionic strength (μ= 1). Solubility of saline soluble proteins (albumin ± globulin) was very poor in either water or 1M NaCl, but increased in 0.4M NaCl at alkaline pH between 7 and 10. Globulins were very soluble in 0.4M NaCl at a pH 9. Albumin was the main storage protein. Saline soluble proteins formed very weak gels.     

Application of parallelized analogical planning to engineering design

Analogical planning provides a means of solving engineering problems where other machine learning methods fail. Unlike many machine learning paradigms, analogy does not require numerous previous examples or a rich domain theory. Instead, analogical planners adapt knowledge of solved problems in similar domains to the current problem. Unfortunately, the analogical planning task is an expensive one. While the process of forming correspondences between a known problem and a new problem is complex, the problem of selecting a base case for the analogy is virtually intractable.This paper addresses the issue of efficiently forming analogical plans. The Anagram planning system is described, which takes advantage of the massively parallel architecture of the Connection Machine to perform base selection and map formation. Anagram provides a tractable solution to analogical planning, with a complexity that is sublinear in the size of the plans.This paper describes the Anagram system and its parallel algorithms. The paper also presents theoretical analyses and empirical results of testing the system on a large database of plans from the domain of automatic programming.     

分布系统中多米诺效应的分析与消除

分布系统中发生故障后,错误信息在进程间的传播,以及由此引起的系统恢复过程中的多米诺效应是分布系统容错恢复技术所面临的最重要与最困难的问题.目前各种研究工作偏重于具体的系统动态恢复技术.本文的研究重点在于首次揭示多米诺效应本身固有的数量特征及其与分布系统技术参数间的联系,给出多米诺效应动态消除技术,引入系统额外开销的下限,并针对动态技术的缺点,探讨多米诺效应的静态消除技术,为解决困难开辟新途径.     

点胶机离线编程软件的设计与开发

SMT设备要达到最大的产量，必须要考虑生产线的效率。点胶机是SMT生产线中的重要设备，因此提高点胶机的生产效率具有十分重要的意义。本文以CAMALOT 5000系统为例，介绍了点胶机离线编程软件的设计与开发中的思想、方法和经验，本文着重探讨了坐标数据的处理和转换，同时针对基于点胶系统优化的TSP问题进行了分析和研究，对程序优化进行了系统分析设计，并编程实现了基本方案。最后在CAMALOT 5000系统上使用本解决方案，大幅度提高了生产效率，证明了本解决方案的优越性和高效性，也为其他SMT设备的离线编程软件的设计提供了一种可参考的思路。     

A globally convergent algorithm for transportation continuous network design problem

The continuous network design problem (CNDP) is characterized by a bilevel programming model, in which the upper level problem is generally to minimize the total system cost under limited expenditure, while at the lower level the network users make choices with regard to route conditions following the user equilibrium principle. In this paper, the bilevel programming model for CNDP is transformed into a single level convex programming problem by virtue of an optimal-value function tool and the relationship between System Optimum (SO) and User Equilibrium (UE). By exploring the inherent nature of the CNDP, the optimal-value function for the lower level user equilibrium problem is proved to be continuously differentiable and its derivative in link capacity enhancement can be obtained efficiently by implementing user equilibrium assignment subroutine. However, the reaction (or response) function between the upper and lower level problem is implicit and its gradient is difficult to obtain. Although, here we approximately express the gradient with the difference concept at each iteration, based on the method of successive averages (MSA), we propose a globally convergent algorithm to solve the single level convex programming problem. Comparing with widely used heuristic algorithms, such as sensitivity analysis based (SAB) method, the proposed algorithm needs not strong hypothesis conditions and complex computation for the inverse matrix. Finally, a numerical example is presented to compare the proposed method with some existing algorithms.     

A branch-and-price algorithm to solve the molten iron allocation problem in iron and steel industry

The molten iron allocation problem (MIAP) is to allocate molten iron from blast furnaces to steel-making furnaces. The allocation needs to observe the release times of the molten iron defined by the draining plan of the blast furnaces and the transport time between the iron-making and steel-making stages. Time window constraints for processing the molten iron must be satisfied to avoid freezing. The objective is to find a schedule with minimum total weighted completion time. This objective reflects the practical consideration of improving steel-making efficiency and reducing operation cost caused by the need for reheating. Such a problem can be viewed as a parallel machine scheduling problem with time windows which is known to be NP-hard. In this paper, we first formulate the molten iron allocation problem as an integer programming model and then reformulate it as a set partitioning model by applying the Dantzig–Wolfe decomposition. We solve the problem using a column generation-based branch-and-price algorithm. Since the subproblem of column generation is still NP-hard, we propose a state-space relaxation-based dynamic programming algorithm for the subproblem. Computational experiments demonstrate that the proposed algorithm is capable of solving problems with up to 100 jobs to optimality within a reasonable computation time.     

QD-Janus: A sequential implementation of Janus in Prolog

Janus is a language designed for distributed constraint programming. This paper describes QD-Janus, a sequential implementation of Janus in Prolog. The compiler uses a number of novel analyses and optimizations to improve the performance of the system. The choice of Prolog as the target language for a compiler, although unusual, is motivated by the following: (i) the semantic gap between Janus and Prolog is much smaller than that between Janus and, say, C or machine language—this simplifies the compilation process significantly, and makes it possible to develop a system with reasonable performance fairly quickly; (ii) recent progress in Prolog implementation techniques, and the development of Prolog systems whose speeds are comparable to those of imperative languages, indicates that the translation to Prolog need not entail a significant performance loss compared to native code compilers; and (iii) compilation to Prolog can benefit immediately from a significant body of work on, and implementations of, parallel Prolog systems. Our experience indicates that translation of logic programming languages to Prolog, accompanied by the development of good program analysis and optimization tools, is an effective way to quickly develop flexible and portable implementations with good performance and low cost.