带性能约束布局问题的全局优化算法

以人造卫星仪器舱布局为例,应用图论,群对集合的作用,轨道与等价关系等刻划各种布局方案的同构,等价类等内在性质,从而首次给出带有性能约束二维布局问题的一个全局优化算法。     

基于改进遗传算法的布局优化子问题

本针对子问题，构造了布局子问题(关于同构布局等价类)的改进遗传算法。将该算法应用于二维布局优化子问题，数值实验表明该算法能够在很好地保持图元的邻接关系的前提下找到子问题的最优解。由于布局优化问题可分解为有限个子问题，所以利用该算法可以找到整个布局优化问题的全局最优解。     

超大规模集成电路布局的优化模型与算法

布局确定集成电路单元在芯片中的具体位置,在单元互不重叠的基础上优化一些性能指标。该问题是NP困难的组合优化问题,是超大规模集成电路物理设计的核心问题之一,对集成电路的性能指标,如线网可布通性、时延、功耗、电路可靠性等有重大影响。在现代的集成电路设计中,布局问题通常包含数百万个集成电路单元,以及大小相异的异质性模块,和各种复杂的布局约束。目前的超大规模集成电路布局算法通常分解为总体布局、布局合法化和详细布局三个步骤。根据近年来集成电路布局算法的研究进展,综述并分析集成电路的总体布局、布局合法化和详细布局的相关优化模型和算法,并展望进一步的研究方向。     

带性能约束的矩形图元布局优化模型及不干涉性算法

本文讨论了以航天卫星仪器舱布局优化设计为背景的、带性能约束的矩形图元布局优化模型及不干涉性判别算法,主要讨论了模型的性质,并将这一模型转化为带反凸约束的凸规划问题。应用文献(4)给出的最优性条件及定界锥分拆算法,可求得带性能约束的矩形图元布局优化问题的全局最优解。     

多层次结构优化方法

本文提出了—种包含虚节点和虚单元的力学模型。称为广义结构;导出了分析广义结构的公式;利用Kuhn-Tucker,条件和满应力准则分别建立了虚单元转为实单元的条件;利用这一条件,可以把结构拓扑优化的非线性规划由混合型转化为连续型,使问题的困难度大为降低。这是一种以单一的尺寸变量为变量的,适用于尺寸优化、几何优化和拓扑、布局优化等各个层次结构优化问题的方法,文内还讨论了用本方法得到的解与总极值的关系,并有几个算例说明方法的有效性。     

一类组合优化函数的若干研究

本文研究了一个组合优化问题.利用组合数论的理论,给出了计算优化函数的一个新方法,并确定了4≤4m≤120时优化函数g(4m,6)的准确值,以及相心的优化向量.     

鲁棒信用风险优化的线性锥优化模型

考虑了具有强健性的信用风险优化问题. 根据最差条件在值风险度量信用风险的方法,建立了信用风险优化问题的模型. 由于信用风险的损失分布存在不确定性,考虑了两类不确定性区间,即箱子型区间和椭球型区间. 把具有强健性的信用风险优化问题分别转化成线性规划问题和二阶锥规划问题. 最后,通过一个信用风险问题的例子来说明此模型的有效性.     

主通道位置不固定的设施布局问题多目标优化模型及算法

以物流中心设施布局问题为对象,提出了考虑出入口及主通道位置不固定情况下的设施布局问题的多目标优化模型并设计了其改进的遗传算法。首先,以物料搬运成本最小、活动关系密切度最大和面积利用率最大为目标,构建了考虑出入口位置不固定条件下的具有I型主通道的设施布局多目标优化数学模型。然后,设计了一种改进的遗传算法,包括:改进的编码、解码方法,追加了解码修正操作,基于惩罚函数策略的适应度函数等。实例测试表明,本算法的执行效率高而且结果稳定,优化效果好,布局结果紧凑适用。     

二维混合布局问题的组合优化模型及算法

本文以卫星仪器舱布局优化设计问题为背景，分别以矩形和圆形为各种仪器的表征图元，建立二维混合布局的组合优化模型，并给出其主要性质和算法     

具有性能约束的三维布局优化模型的主要性质

本文研究了简化的旋转卫星舱内的三维布局优化问题,建立了一个具有性能约束的三维布局优化模型,给出了其主要性质,并证明了性能目标函数为局部Lipschitz连续函数,且其局部最优解即为全局最优解.     

卫星舱布局的半无限优化模型及最优性条件

本文以人造卫星仪器舱布局问题为背景，建立了一个半无限优化模型。应用图论、群对集合的作用、轨道等，把该问题分解为有限多个子问题，在每个子问题中克服了关于优化变量的时断时续性质。针对每个子问题分析了模型中各函数的性质，并构造了一个局部等价于子问题的极大极小问题。利用这个极大极小问题及子问题中各函数的方向可微性给出了子问题的一阶最优性条件。     

The layout problem of two kinds of graph elements with performance constraints and its optimality conditions

This paper presents an optimization model with performance constraints for two kinds of graph elements layout problem. The layout problem is partitioned into finite subproblems by using graph theory and group theory, such that each subproblem overcomes its on-off nature about optimal variable. Furthermore each subproblem is relaxed and the continuity about optimal variable doesn’t change. We construct a min-max problem which is locally equivalent to the relaxed subproblem and develop the first order necessary and sufficient conditions for the relaxed subproblem by virtue of the min-max problem and the theories of convex analysis and nonsmooth optimization. The global optimal solution can be obtained through the first order optimality conditions.     

An algorithm of global optimization for solving layout problems

The two-dimensional layout problem is known to be NP-complete, and the current research work is basically in the heuristic way. In this paper, we mainly discuss the methods for solving layout problem about the artificial satellite module by virtue of graph theory and group theory. Also, an algorithm of global optimization is presented first time. The method given here can be extended to solve other type of layout problems.     

The Model for Two-dimensional Layout Optimization Problem with Performance Constraints and Its Optimality Function

This paper studies the two-dimensional layout optimization problem.An optimization model withperformance constraints is presented.The layout problem is partitioned into finite subproblems in terms ofgraph theory,in such a way of that each subproblem overcomes its on-off nature optimal variable.A minimaxproblem is constructed that is locally equivalent to each subproblem.By using this minimax problem,we presentthe optimality function for every subproblem and prove that the first order necessary optimality condition issatisfied at a point if and only if this point is a zero of optimality function.     

卫星舱三维布局优化模型及判断不干涉性算法

本以人造卫星仪器舱布局问题为背景。建立了在抛物圆柱体空间中带性能约束的长方体群的布局优化模型。分析模型中不干涉性约束的性质，利用凸集分离定理给出了等价的显式表达式，并构造了判断不干涉性的算法。     

一种高压开关产品的装配过程优化问题研究

本文针对高压开关产品的装配线提出一个实际的装配过程优化问题:高压开关产品的装配过程优化问题。该问题是在传统的空间布局问题中,加入了装配线工艺流程约束,是一类新的优化问题。本文为该问题建立了整数规划模型,并为该模型开发了启发式算法。然后以ZF11-252产品的装配过程为例,采用启发式算法求解模型。     

Optimization of generalized desirability functions under model uncertainty

Desirability functions are increasingly used in multi-criteria decision-making which we support by modern optimization. It is necessary to formulate desirability functions to obtain a generalized version with a piecewise max type-structure for optimizing them in different areas of mathematics, operational research, management science and engineering by nonsmooth optimization approaches. This optimization problem needs to be robustified as regression models employed by the desirability functions are typically built under lack of knowledge about the underlying model. In this paper, we contribute to the theory of desirability functions by our robustification approach. We present how generalized semi-infinite programming and disjunctive optimization can be used for this purpose. We show our findings on a numerical example. The robustification of the optimization problem eventually aims at variance reduction in the optimal solutions.     

Convergence and Application of a Decomposition Method Using Duality Bounds for Nonconvex Global Optimization

The subject of this article is a class of global optimization problems, in which the variables can be divided into two groups such that, in each group, the functions involved have the same structure (e.g. linear, convex or concave, etc.). Based on the decomposition idea of Benders (Ref. 1), a corresponding master problem is defined on the space of one of the two groups of variables. The objective function of this master problem is in fact the optimal value function of a nonlinear parametric optimization problem. To solve the resulting master problem, a branch-and-bound scheme is proposed, in which the estimation of the lower bounds is performed by applying the well-known weak duality theorem in Lagrange duality. The results of this article concentrate on two subjects: investigating the convergence of the general algorithm and solving dual problems of some special classes of nonconvex optimization problems. Based on results in sensitivity and stability theory and in parametric optimization, conditions for the convergence are established by investigating the so-called dual properness property and the upper semicontinuity of the objective function of the master problem. The general algorithm is then discussed in detail for some nonconvex problems including concave minimization problems with a special structure, general quadratic problems, optimization problems on the efficient set, and linear multiplicative programming problems.