线性规划在燃气梭式窑中应用初探

本文尝试将线性规划技术应用到燃气梭式窑的操作管理中。叙述了线性规划模型（ＬＰＭ）的建立过程及求解过程中利用改进单纯形法加快收敛速度的理论基础，并在计算上进行模拟分析，得出的结果与理论分析相吻合。     

企业年度产品数据分析与多元优化

分析了企业生产现状及其相关数据和资料,利用多元线性规划理论,建立了年度生产计划的数学模型,并应用计算机Excel软件,对线性规划问题进行求解,获得了较为合理的年度生产计划。     

基于模糊预测型线性规划模型的矿山产能配置

将线性规划与模糊数学及灰色理论有机结合,构建了与产能分配实际情况较为接近的模糊预测型线性规划模型.利用灰色预测理论对各灰色系数进行白化,将模糊预测型线性规划模型转化为模糊线性规划模型,利用最优判决条件进一步转化,得到以最大隶属度为目标函数的一般线性规划模型,求解得到了矿山的最优产能分配,以实现矿山产能的科学配置和效益的最大化.     

纸浆洗涤过程的优化研究(Ⅱ)

主要利用不等式约束的非线性规划理论,研究纸浆洗涤过程的优化。依据已建立的稳态神经网络模型,采用外罚函数法对该过程进行优化计算,得到的优化结果用于实际过程,达到了较好的效果。     

正交多项回归和最优化方法在胶粘剂制备中的应用

本试验是在胶粘剂乳液制备过程中,采用正交多项回归法,建立乳液制备过程的数学模型,然后运用线性规划和非线性规划对数学模型进行最优化,为控制聚合反应条件、预测试验结果和制订最佳工艺条件和配方提供理论依据。     

大型矿山生产系统的模糊线性规划

针对非确定性环境中大型矿山生产系统规划管理问题,采用模糊数学理论模拟分析非确定性矿山生产规划问题,给出了在多种配置、多种产品、多水平层次、多循环周期物流网络中的模糊线性规划(FLP)模型。通过工程实例计算分析表明,采用模糊线性规划方法确定出的矿山生产规划方案符合工程实际。     

线性规划在浮法玻璃配方设计中的应用

在浮法玻璃生产线的设计与生产过程中 ,运用线性规划原理 ,优化玻璃配方 ,实现原料成本的最低化。     

线性规划单纯形算法程序简介

(一)线性规划单纯形算法的数学模型 创立于本世纪四十年代的线性规划(简称LP),是运筹学的一个重要分支。它是系统工程学的主要理论基础之一,也是规划论中应用最有效、最广泛的一种优化方法。 1947年,美国著名数学家丹齐格首先提出了单纯形算法。单纯形算法是解决一切线性规划问题的第一种,也是迄今应用最广泛和最有效的算法。它是在各种相关的多变量线性约束条件下,用数学方法求解所研究对     

苯胺生产的节能与优化

本文利用非线性规划方法对影响苯胺生产经济效益的硝基苯还原终点、苯胺精制塔回流比及理论板数进行优化计算,得到了最经济的生产条件,并给出了描述苯胺精制塔理论板数、回流比及原料中硝基苯含量的解析表达式。     

基于Kubelka-Munk理论的线性规划配色法

以Kubelka-Munk理论为基础,提出了一种计算涂料配色的线性规划方法以及简捷获取基     

Exxon experience with large scale linear and nonlinear programming applications

Exxon has been a large user of linear programming since its introduction. Exxon's primary large scale math programming system has evolved to also include facilities for sucessive linear programming and mixed integer programming. Some of Exxon's other math programming tools for quadratic programming and succesive quadratic programming are also described in this paper. Results of a recent study conducted to compare the performance of Exxon's succesive linear programming and successive quadratic programming techniques with the reduced gradient technology employed in other programs are presented.     

Application of mixed-integer linear programming in multiterm expansion planning under multiobjectives

A procedure to expand plant capacities over a time horizon is presented under multiobjectives. A stepwise interactive approach has been proposed to formulate a problem that is small but complete enough to provide a best-compromise solution for decision-making. The approach relies on the relaxation of flexible constraints and the sensitivity analysis of linear programming. It yields the significant feature of identifying the expansion increments associated with specific objectives or with structural infeasibility. The resulting multiobjective mixed-integer linear programming problem was solved advantageously by an interactive goal programming algorithm. An illustrative example is provided to clarify the procedure and show its computational effectiveness.     

Energy optimization in heat integrated water allocation networks

In this paper, linear programming formulations, complemented by concept based pinch analysis results, are developed to target the minimum energy requirements in a heat integrated fixed flow rate water allocation networks. These formulations can be applied for the cases of heat integration through isothermal and non-isothermal mixing in water allocation networks involving single as well as multiple contaminants. The earlier reported approaches are based on linear programming formulation for the case of isothermal mixing and either mixed integer non-linear programming or discontinuous non-linear programming formulations for the case of non-isothermal mixing. It has been observed that the earlier reported methodologies produce sub-optimal results for the case of non-isothermal mixing. However, the proposed methodologies produce the optimum results because of the rigorously proved linear formulation. Utility requirements for isothermal as well as for non-isothermal mixing cases are compared over a range of minimum approach temperatures, to evaluate the energy performance using illustrative examples.     

Application of Plackett-Burman design and linear programming to light-duty liquid detergent formulation

Plackett-Burman experimental design is applied to a seven-component light-duty liquid detergent formulation to determine which components affect five different properties of the formulation. Regression analysis and linear programming are then applied to the results of the Plackett-Burman analysis. It is shown that the formulation can be optimized by linear programming, even if some of the properties are nonlinear. The procedure saves much of the experimental effort required to find the quadratic and interaction terms for nonlinear models of the properties and the difficulties of optimization with nonlinear constraints.     

A New Approach to Linear Temperature Programming Calculations

Abstract

The theory of temperature programming has been reexamined. It is shown that a linear program leads to an explicit relation for the retention temperature in terms of the inverse exponential integral. Numerical examples are solved using a straight line plot of the exponential integral together with a plot based on the equivalent temperature concept. A simple explicit expression in terms of common functions for the retention temperature during linear temperature programming was deduced. This was made possible using the inverse log nonlinear program which can be made to approximate quite closely a linear program. This expression was used to explain the constancy of intervals and other phenomena encountered during the linear temperature programming of homologous series.     

毛细管气相色谱法测定MDI级苯胺中的微量苯酚

采用气相色谱法,色谱柱为HP—5型,30m×0.32mm×1.0μm毛细管柱,N2为载气,分流比20∶1,运用程序升温和程序流量模式,外标法测定MDI级苯胺中微量苯酚的含量。得到线性回归方程为y=0.305 3x-0.829 1,相关系数r2=0.999 3,标准偏差小于0.5%(n=8),平均回收率99.36%～100.64%。该方法操作简便、快速,能满足MDI级苯胺的检测要求。     

需求不确定下炼油企业生产计划优化混合规划模型

Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty, and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently, piecewise linear approximation functions are derived and applied to solve the hybrid programming model-under uniform distribution assumption. Case studies show that the linear approximation algorithm is effective to solve.the hybrid programming model, along with an error≤0.5% when the deviatiorgmean≤20%. The simulation results indicate that the hybrid programming model with an appropriate weight factor （0.1-0.2） can effectively improve the optimal operational strategies under demand uncertainty, achieving higher profit than the linear programming model and the stochastic programming one with about 1.3% and 0.4% enhancement, respectavely.     

Linear programming formulations for attainable region analysis

We propose linear programming (LP) models for attainable region (AR) analysis by considering a rate vector field in concentration space with an arbitrarily large number of points. One model provides a method to construct candidate ARs using a fully connected network of continuously stirred tank reactors (CSTRs) of arbitrary volume. More importantly, these methods are extended to derive linear programming conditions that are stronger necessary conditions than have proposed previously by Glasser and Hildebrandt. We state the LP condition as: No combination of nonzero volume CSTRs, operating at discretized points in the complement of the candidate AR, can extend the region. We demonstrate these proposed linear programming techniques on several two-dimensional reaction mechanisms and then apply the LP methods to verify extensions for a previously published three-dimensional candidate AR.