Barlow-wu continuum systems: A discussion on the model

Summary Barlow-Wu continuum structure functions have been introduced in the past as one particularly interesting family of continuum structure functions. In this paper we provide an alternative characterization for such continuum structure functions, showing other interesting properties. Research supported by Dirección General de Investigación Científica y Técnica (DGICYT), national grants number PB91-0389 and number BE91-225.     

参数曲线的全局凸性判别条件

基于平面曲线的二次微商,导出了二重点的判别条件,结合参数曲线的局部凸性条件,得到了参数闭曲线的充要条件。给出了参数曲线的拐点判别条件,从而得到了参数曲线局部凸的充要条件。     

Relaxed robust second-order-cone programming

In this paper, we propose an approximate optimization model for the robust second-order-cone programming problem with a single-ellipsoid uncertainty set for which the computational complexity is not known yet. We prove that this approximate robust model can be equivalently reformulated as a finite convex optimization problem.     

Optimal solutions for unrelated parallel machines scheduling problems using convex quadratic reformulations

In this work, we take advantage of the powerful quadratic programming theory to obtain optimal solutions of scheduling problems. We apply a methodology that starts, in contrast to more classical approaches, by formulating three unrelated parallel machine scheduling problems as 0–1 quadratic programs under linear constraints. By construction, these quadratic programs are non-convex. Therefore, before submitting them to a branch-and-bound procedure, we reformulate them in such a way that we can ensure convexity and a high-quality continuous lower bound. Experimental results show that this methodology is interesting by obtaining the best results in literature for two of the three studied scheduling problems.     

Geometric Condition Measures and Smoothness Condition Measures for Closed Convex Sets and Linear Regularity of Infinitely Many Closed Convex Sets

In this paper, we study geometric condition measures and smoothness condition measures of closed convex sets, bounded linear regularity, and linear regularity. We show that, under certain conditions, the constant for the linear regularity of infinitely many closed convex sets can be characterized by the geometric condition measure of the intersection or by the smoothness condition measure of the intersection. We study also the bounded linear regularity and present some interesting properties of the general linear regularity problem.The author is grateful to the referees for valuable and constructive suggestions. In particular, she thanks a referee for drawing her attention to Corollary 5.14 of Ref. 3, which inspired her to derive Theorem 4.2 and Corollary 4.2 in the revision of this paper.     

严格端点与多面体形赋范空间

本文研究了凸α-体的切锥,切流形及切空间与凸α-体的Minkowski泛函的次微分之间的关系.对于凸α-体的每个代数边界点,存在一个拟直和分解使按代数意义该边界点既是一个子空间的光滑点又是拟余子空间的严格端点.所获一般结论可有效地用于多面体形赋范空间理论.     

Duality in robust optimization: Primal worst equals dual best

We study the dual problems associated with the robust counterparts of uncertain convex programs. We show that while the primal robust problem corresponds to a decision maker operating under the worst possible data, the dual problem corresponds to a decision maker operating under the best possible data.     

A converse to the Eidelheit theorem in real Hilbert spaces

We establish the following converse to the Eidelheit theorem: an unbounded closed and convex set of a real Hilbert space may be separated by a closed hyperplane from every other disjoint closed and convex set, if and only if it has a finite codimension and a non-empty interior with respect to its affine hull.     

N 元指数和对数平均的凸性及几何凸性

讨论了n 元指数平均和对数平均的凸性、S - 凸性、几何凸性及S - 几何凸性, 证明了:(1) n 元指数平均是S - 凹的和S - 几何凸的; (2) n 元第一对数平均是S - 凹的; (3) n 元第二对数平均是凹的和几何凸的. 最后提出了二个悬而未决的问题.     

A convex analysis approach for convex multiplicative programming

Global optimization problems involving the minimization of a product of convex functions on a convex set are addressed in this paper. Elements of convex analysis are used to obtain a suitable representation of the convex multiplicative problem in the outcome space, where its global solution is reduced to the solution of a sequence of quasiconcave minimizations on polytopes. Computational experiments illustrate the performance of the global optimization algorithm proposed.