易拉罐形状和尺寸的最优设计

研究易拉罐形状及尺寸的最优设计分析问题.首先,根据实际测量的数据,利用拉格朗日乘子法,验证了市售易拉罐设计尺寸的合理性与实用性.其次,给出了个性化的创新型美观设计方案,力求以节约材料和使用方面的优势征服厂家和消费者.最后,利用辛普生公式近似算法,得到了新造型设计的具体尺寸.     

易拉罐形状和尺寸的最优设计模型

用游标卡尺测量了当前流行的几种易拉罐饮料尺寸参数,然后建立微分方程模型和规划模型,借助MATLAB 6.5,LINGO8.0编程求解出了易拉罐为正圆柱体、圆台和圆柱体的组合体时的最优设计.最后综合经济、美观、实用等因素,运用非线性规划和层次分析法得出设想中易拉罐的最佳设计,对2006"高教社杯"全国数学建模竞赛C题中的各问题作出了完整的解答.     

椭球体易拉罐形状和尺寸的优化设计模型

从材料最省、外观最美、放置稳定的角度设计了"椭球体"易拉罐的形状,然后通过建立非线性规划模型Ⅰ,求出了"椭球体"易拉罐的中腰半径、底面半径和高度.然后从手感舒适的角度建立了优化模型Ⅱ,从而确定了两种型号的"椭球体"易拉罐的最优尺寸.     

天然气管道订购和运输的最优设计

本文对天然气主管道钢管的订购和铺设计划问题建立了求解小费用的模型,对于问题一,建立了半正定二次规划模型,得出最小费用为127.8632亿元,对于问题二,定义了两个评估函数,给出了销价变化与总费用,订购计划和运动计划的关系,产量上限的变化对总费用,订购计划和运输计划的影响,对于问题三,通过引入邻接矩阵和边长矩阵的概念,建立了一个用于求解树状在定二次规划模型,这个扩展模型,可以用于求解网装结构,将图二所给数据代入模型,求得的最小费用为140．6631亿元,考虑到问题中的假设,我们对所求得的结果进行了适当修正。     

易拉罐的优化设计

本文讲述了"易拉罐形状和尺寸的最优设计"问题的命题、建模和求解,评述了学生递交的论文中的优缺点,提出了若干建议.     

混料模型的混合最优设计

最优设计是试验设计中必不可少的一种设计方法,混合最优设计是二步最优设计中一种常见的应用。本文以混料模型为基础,提出一种新的寻求混合最优设计的方法,并以此方法解决了混料模型的混合最优设计问题。     

钻井布局的最优设计

本文讨论了钻井布局的最优策略问题,建立了一个最优化模型,针对题目的三个问题,提出了重要定理1,必要条件1、2,在此基础上计算并证明了问题1中可利用的旧井最多为（P2,P4,P5,P10）四只。又借助最大团理论,计算机搜索得总问题2中可利用的旧井最多为（P1,P6,P7,P8,P9,P11）6口,并对此进行了证明,对于问题3;运用定理1给出并证明了利用n口旧井的充分必要条件及实现它的算法。模型求解采用MATLAB软件,计算结果表明本文采用的算法简便可行,并具有一定的推广价值。     

超立方体上的多元线性回归模型的最优设计

对n维超立方体上的多元线性回归模型采用2n个顶点进行均匀测度设计,证明了该设计在Iλ最优准则及D、A最优准则下都是最优设计,并给出了n=2,3时的最小二乘估计.     

步进应力加速寿命试验的最优设计

本文在一般k个未知参数的加速方程下,以MLE渐近方差最小为准则,解决了指数分布时k个应力情况的最优设计问题.     

多重混料系统及其最优设计

本文主要讨论了多重混料系统上Scheff\'{e}模型的最优设计问题. 在本文中, 提出并证明了一个基于单纯形和正定二次型的不等式, 并应用这个不等式解决了多重混料系统上多项式模型的$D$-最优和$A$-最优设计的结构问题, 找到了一个构造最优设计的新方法.     

JOINT MODEL AND CRITERION OPTIMAL EXPERIMENT DESIGN

In this paper,a new optimal design criterion--joint model and criterion optimal de-sign criterioon is put forward. The design that is subject to this criterion satisfies many kinds of lin-ear optimal criterion and D-optimal criterion on several experiment models at the same time. Theequivalent condition of this optimal design is given. Its iterative algorithm and the algorithm cover-genee are stated.     

On an optimal shape design problem to control a thermoelastic deformation under a prescribed thermal treatment

A shape optimization problem concerned with thermal deformation of elastic bodies is considered. In this article, measure theory approach in function space is derived, resulting in an effective algorithm for the discretized optimization problem. First the problem is expressed as an optimal control problem governed by variational forms on a fixed domain. Then by using an embedding method, the class of admissible shapes is replaced by a class of positive Borel measures. The optimization problem in measure space is then approximated by a linear programming problem. The optimal measure representing optimal shape is approximated by the solution of this finite-dimensional linear programming problem. Numerical examples are also given.     

Optimal design of pitched laminated wood beams

The optimal design of a pitched laminated wood beam is considered. An engineering formulation is given in which the volume of the beam is minimized. The problem is then reformulated and solved as a generalized geometric (signomial) program. Sample designs are presented.This research was partially supported by the Office of Naval Research under Contracts Nos. N00014-75-C-0267 and N00014-75-C-0865; by the US Energy Research and Development Administration Contract No. E(04-3)-326 PA-18; and by the National Science Foundation, Grant No. DCR75-04544 at Stanford University. This work was carried out during the first author's stay at the Management Science Division of the University of British Columbia and the Systems Optimization Laboratory of Stanford University. The authors are indebted to Mr. S. Liu and Mrs. M. Ratner for their assistance in performing the computations.     

Parametric optimal design

Two algorithms for the solution of a parametric optimal design problem are developed and applied to example problems from diverse fields, such as finite allocation problems, optimal design of dynamical systems, and Chebyshev approximation. Sensitivity analysis gives rise to a first-order feedback law, which contains a compensating term for any error in the nominal solution, as well as sensitivity of the solution with respect to design parameters. The compensating term, when used alone, leads to a new second-order method of maximization for a linearly-constrained nonlinear programming problem.This paper is based on the PhD Thesis of the first author.     

The optimal design for hypothesis test and its application in genetic linkage analysis

This paper proposes a class of linear models with inequable variance, based on background in genetic linkage analysis, and considers the optimal design problem for the hypothesis test of the parameters in such models. To assess a design for the test, a frame of decision theory is established. Under this frame, an admissible minimax design is obtained. It is shown to be not only admissible and minimax in genetic linkage analysis, but best among a reasonable subclass of designs. The power of the test in genetic linkage analysis is substantially improved by using this optimal design.     

A refined Newton’s mesh independence principle for a class of optimal shape design problems

Shape optimization is described by finding the geometry of a structure which is optimal in the sense of a minimized cost function with respect to certain constraints. A Newton’s mesh independence principle was very efficiently used to solve a certain class of optimal design problems in [6]. Here motivated by optimization considerations we show that under the same computational cost an even finer mesh independence principle can be given.     

On the optimal design of plates for a given deflection

The optimum design problem of an elastic plate for a given deflection is considered. The design variable is chosen to be the thickness of the plate. Using the principle of stationary mutual potential energy first introduced by Shield and Prager, a sufficient optimality condition (which makes the volume stationary) is derived for plates under bending caused by general loading conditions. As an example, the optimum profile of a simply supported circular plate under a given rotationally symmetric loading is obtained.     

Survivable network design under optimal and heuristic interdiction scenarios

We examine the problem of building or fortifying a network to defend against enemy attacks in various scenarios. In particular, we examine the case in which an enemy can destroy any portion of any arc that a designer constructs on the network, subject to some interdiction budget. This problem takes the form of a three-level, two-player game, in which the designer acts first to construct a network and transmit an initial set of flows through the network. The enemy acts next to destroy a set of constructed arcs in the designer’s network, and the designer acts last to transmit a final set of flows in the network. Most studies of this nature assume that the enemy will act optimally; however, in real-world scenarios one cannot necessarily assume rationality on the part of the enemy. Hence, we prescribe optimal network design algorithms for three different profiles of enemy action: an enemy destroying arcs based on capacities, based on initial flows, or acting optimally to minimize our maximum profits obtained from transmitting flows.     

Geometry of optimal value functions with applications to redundancy in linear programming

In 1967, Wets and Witzgall (Ref. 1) made, in passing, a connection between frames of polyhedral cones and redundancy in linear programming. The present work elaborates and formalizes the theoretical details needed to establish this relation. We study the properties of optimal value functions in order to derive the correspondence between problems in redundancy and the frame of a polyhedral cone. The insights obtained lead to schemes to improve the efficiency of procedures to detect redundancy in the areas of linear programming, stochastic programming, and computational geometry.The author is indebted to G. Dewan for his review and discussions.     

On the optimal design of tandem queueing systems with finite buffers

We consider tandem queueing systems that can be formulated as a continuous-time Markov chain, and investigate how to maximize the throughput when the queue capacities are limited. We consider various constrained optimization problems where the decision variables are of one or more of the following types: (1) expected service times, (2) queue capacities, and (3) the number of servers at the respective stations. After surveying our previous studies of this kind, we open up consideration of three new problems by presenting some numerical results that should give some insight into the general form of the optimal design.