Generalizations of Slater's constraint qualification for infinite convex programs

In this paper we study constraint qualifications and duality results for infinite convex programs (P) = inf{f(x): g(x) – S, x C}, whereg = (g ₁,g ₂) andS = S ₁ ×S ₂,S _i are convex cones,i = 1, 2,C is a convex subset of a vector spaceX, andf andg _i are, respectively, convex andS _i -convex,i = 1, 2. In particular, we consider the special case whenS ₂ is in afinite dimensional space,g ₂ is affine andS ₂ is polyhedral. We show that a recently introduced simple constraint qualification, and the so-called quasi relative interior constraint qualification both extend to (P), from the special case thatg = g ₂ is affine andS = S ₂ is polyhedral in a finite dimensional space (the so-called partially finite program). This provides generalized Slater type conditions for (P) which are much weaker than the standard Slater condition. We exhibit the relationship between these two constraint qualifications and show how to replace the affine assumption ong ₂ and the finite dimensionality assumption onS ₂, by a local compactness assumption. We then introduce the notion of strong quasi relative interior to get parallel results for more general infinite dimensional programs without the local compactness assumption. Our basic tool reduces to guaranteeing the closure of the sum of two closed convex cones.     

ε-optimality criteria for convex programming problems via exact penalty functions

In this paper, we present-optimality criteria for convex programming problems associated with exact penalty functions. Several authors have given various criteria under the assumption that such convex problems and the associated dual problems can be solved. We assume the solvability of neither the convex problem nor the dual problem. To derive our criteria, we estimate the size of the penalty parameter in terms of an-solution for the dual problem.     

Value function and optimality conditions for semilinear control problems

This paper is concerned with optimal control problems of Mayer and Bolza type for systems governed by a semilinear state equationx(t)=Ax(t) + f(t, x(t), u(t)), u(t) U, whereA is the infinitesimal generator of a strongly continuous semigroup in a Banach spaceX. We prove necessary and sufficient conditions for optimality and then use these conditions to investigate properties of the value function related to superdifferentials. Conversely, we use the value function to obtain criteria for optimality and feedback systems.Work (partially) supported by the Research Project Equazioni di evoluzione e applicazioni fisicomatematiche (M.U.R.S.T.-Italy).     

Higher-order necessary conditions for infinite and semi-infinite optimization

In this paper, we present a unified theory of first-order and higher-order necessary optimality conditions for abstract vector optimization problems in normed linear spaces. We prove general multiplier rules, from which nearly all known first-order, second-order, and higher-order necessary conditions can be derived. In the last section, we prove higher-order necessary conditions for semi-infinite programming problems.This work was developed within the Forschungsschwerpunkt Dynamische Systeme, Universität Bremen, Bremen, West Germany.The author wishes to thank Prof. Dr. D. Hinrichsen for his helpful remarks and discussions during the preparation of this work.     

Improving splitless injection with electronic pressure programming

An experimental injection port has been designed for split or splitless sample introduction in capillary gas chromatography; the inlet uses electronic pressure control, in order that the column head pressure may be set from the GC keyboard, and the inlet may be used in the constant flow or constant pressure modes. Alternatively, the column head pressure may be programmed up or down during a GC run in a manner analogous to even temperature programming. Using electronic pressure control, a method was developed which used high column head pressures (high column flow rates) at the time of injection, followed by rapid reduction of the pressure to that required for optimum GC separation. In this way, high flow rates could be used at the time of splitless injection to reduce sample discrimination, while lower flow rates could be used for the separation. Using this method, up to 5 μl of a test sample could be injected in the splitless mode with no discrimination; in another experiment, 2.3 times as much sample was introduced into the column by using electronic pressure programming. Some GC peak broadening was observed in the first experiment.     

Stability theorems for infinitely constrained mathematical programs

The primary concern of this paper is to investigate stability conditions for the mathematical program: findx E ⁿ that maximizesf(x):g ^j(x)0 for somej J, wheref is a real scalarvalued function and eachg is a real vector-valued function of possibly infinite dimension. It should be noted that we allow, possibly infinitely many, disjunctive forms. In an earlier work, Evans and Gould established stability theorems wheng is a continuous finite-dimensional real-vector function andJ=1. It is pointed out that the results of this paper reduce to the Evans-Gould results under their assumptions. Furthermore, since we use a slightly more general definition of lower and upper semicontinuous point-to-set mappings, we can dispense with the continuity ofg (except in a few instances where it is implied by convexity assumptions).     

关于凸规划对偶模型的讨论

修正了文[1]中的错误,在其基础上讨论了凸规划的Lagrange对偶,Subgradient对偶及Wolfe对偶等四种对偶模型之间的关系,给出了它们之间等价的条件.     

一种求解混合整数非线性规划问题的演化算法--搜索空间自动收缩法

提出一种求解混合整数非线性规划问题的新的演化算法 -搜索空间自动收缩法 (ACSSOS) .在这种算法中 ,演化算法既用来定位最优解区域 ,实现搜索空间自动向全局最优解收缩 ,又用来最终求得最优解 .由于在遗传算子中引用了舍入操作 ,它不仅可用来求解混合非线性整数规划问题 ,也可求解纯整型或纯实型变量非线性函数优化问题 .数值试验结果表明本文的算法在解的质量、稳定性和收敛速度等方面优于一般的演化算法 .     

凸二次规划的投影收缩算法

对于一般的凸二次规划问题,首先结合该问题的对偶问题给出了解的充分必要条件,然后给出了一种解决该问题的投影收缩算法,并证明了该投影收缩算法的总体收敛性.     

高阶常微分方程的动态演化建模

提出了采用高阶常微分方程模型代替传统时序分析中所用的ARMA模型来实现一维时间序列的建模和预报．设计的将遗传程序设计与遗传算法相嵌套的动态演化建模算法,用遗传程序设计优化模型结构,以遗传算法优化模型参数,边收集数据边建模边预报,首次成功地实现了时间序列实时预报的程序自动化．两个时间序列的应用实例表明采用此算法可获得较好的实时预报效果．