Separating the solution sets of analytical and polynomial systems

A linear inequality system with infinitely many constraints is polynomial (analytical) if its index set is a compact interval of the real line and all its coefficients are polynomial (analytical, respectively) functions of the index on this interval. This paper provides an example of analytical system whose solution set cannot be the solution set of any polynomial system. Research supported by DGES of Spain and FEDER of UE, Grant BFM2002-04114-C02-01. Research supported by CONACyT of Mexico, Grant 130036. Research partially supported by CONACyT of Mexico, Grant 44003.     

On Exiting After Voting

We consider the problem of a society whose members must choose from a finite set of alternatives. After knowing the chosen alternative, members may reconsider their membership by either staying or exiting. In turn, and as a consequence of the exit of some of its members, other members might now find undesirable to belong to the society as well. For general exit procedures we analyze the exit behavior of members after knowing the chosen alternative. For the case of monotonic preferences we propose, for each chosen alternative, an unambiguous and meaningful prediction of the subset of members that will exitWe thank Salvador Barberà, Carmen Beviá, David Cantala, Howard Petith, William Thomson, Marc Vorsatz, and Associate Editor, and two anonymous referees for their helpful comments and suggestions. The work of D. Berga is partially supported by Research Grants 9101100 from the Universitat de Girona, and also by AGL2001-2333-C02-01 and SEJ2004-03276 from the Spanish Ministry of Science and Technology and from the Spanish Ministry of Education and Science, respectively. The work of G. Bergantiñ os is partially supported by Research Grants BEC2002-04102-C02-01 from the Spanish Ministry of Science and Technology and PGIDIT03PXIC30002PN from the Xunta de Galicia. The work of J. Massó is partially supported by Research Grants BEC2002-02130 from the Spanish Ministry of Science and Technology and 2001SGR-00162 from the Generalitat de Catalunya. The work of D. Berga and J. Massó is also partially supported by the Barcelona Economics Program (CREA). The work of A. Neme is partially supported by Research Grant 319502 from the Universidad Nacional de San Luis     

Hedging Interest Rate Risk by Optimization in Banach Spaces

This paper addresses the hedging of bond portfolios interest rate risk by drawing on the classical one-period no-arbitrage approach of financial economics. Under quite weak assumptions, several maximin portfolios are introduced by means of semi-infinite mathematical programming problems. These problems involve several Banach spaces; consequently, infinite-dimensional versions of classical algorithms are required. Furthermore, the corresponding solutions satisfy a saddle-point condition illustrating how they may provide appropriate hedging with respect to the interest rate risk. Communicated by D. G. Luenberger This research was partially supported by the Comunidad Autonoma de Madrid (Spain), Grant 06/HSE/0150/2004, and by MEyC (Spain), Grants BEC2000-1388-C04-03 and BEC2000-0167. The authors thank the unknown reviewer whose suggestions have led to significant improvements of the paper.     

The Serial Property and Restricted Balanced Contributions in discrete cost sharing problems

We show that the Serial Poperty and Restricted Balanced Contributions characterize the subsidy-free serial cost sharing method (Moulin (1995)) in discrete cost allocation problems. This research has been partially supported by the Universidad del País Vasco (project UPV 00031.321-15352/2003), MCyT under projects BEC2003-08182 and SEJ2004-07554, and by the Generalitat Valenciana under project GRUPOS04/13.     

Solving geometric programs using GRG: Results and comparisons

This paper describes the performance of a general-purpose GRG code for nonlinear programming in solving geometric programs. The main conclusions drawn from the experiments reported are: (i) GRG competes well with special-purpose geometric programming codes in solving geometric programs; and (ii) standard time, as defined by Colville, is an inadequate means of compensating for different computing environments while comparing optimization algorithms.This research was partially supported by the Office of Naval Research under Contracts Nos. N00014-75-C-0267 and N00014-75-C-0865, the US Energy Research and Development Administration, Contract No. E(04-3)-326 PA-18, and the National Science Foundation, Grant No. DCR75-04544 at Stanford University; and by the Office of Naval Research under Contract No. N00014-75-C-0240, and the National Science Foundation, Grant No. SOC74-23808, at Case Western Reserve University.     

Best Approximation and Perturbation Property in Hilbert Spaces

We study the perturbation property of best approximation to a set defined by an abstract nonlinear constraint system. We show that, at a normal point, the perturbation property of best approximation is equivalent to an equality expressed in terms of normal cones. This equality is related to the strong conical hull intersection property. Our results generalize many known results in the literature on perturbation property of best approximation established for a set defined by a finite system of linear/nonlinear inequalities. The connection to minimization problem is considered.The authors thank the referees for valuable suggestions.K.F. Ng - This author was partially supported by Grant A0324638 from the National Natural Science Foundation of China and Grants (2001) 01GY051-66 and SZD0406 from Sichuan Province. Y.R. He -This author was supported by a Direct Grant (CUHK) and an Earmarked Grant from the Research Grant Council of Hong Kong.     

Solving variational inequalities defined on a domain with infinitely many linear constraints

We study a variational inequality problem whose domain is defined by infinitely many linear inequalities. A discretization method and an analytic center based inexact cutting plane method are proposed. Under proper assumptions, the convergence results for both methods are given. We also provide numerical examples to illustrate the proposed methods. The work of S. Wu was partially supported by the National Science Council, Taiwan, ROC (Grant No. 19731001). S.-C. Fang’s research has been supported by the US Army Research Office (Grant No. W911NF-04-D-0003) and National Science Foundation (Grant No. DMI-0553310).     

Primal-Dual Simplex Method for Multiobjective Linear Programming

We develop a primal-dual simplex algorithm for multicriteria linear programming. It is based on the scalarization theorem of Pareto optimal solutions of multicriteria linear programs and the single objective primal-dual simplex algorithm. We illustrate the algorithm by an example, present some numerical results, give some further details on special cases and point out future research. The paper was written during a visit of the first author to the University of Sevilla financed by a grant of the Andalusian Consejería de Educación. The research of the first author was partially supported by University of Auckland Grant 3602178/9275. The research of the second and third authors was partially financed by Spanish Grants BFM2001-2378, BFM2001-4028, MTM2004-0909 and HA2003-0121. We thank Anthony Przybylski for the implementation and making his results available. We thank the anonymous referees, whose comments have helped us to improve the presentation of the paper.     

Numerical Comparison of Augmented Lagrangian Algorithms for Nonconvex Problems

Augmented Lagrangian algorithms are very popular tools for solving nonlinear programming problems. At each outer iteration of these methods a simpler optimization problem is solved, for which efficient algorithms can be used, especially when the problems are large. The most famous Augmented Lagrangian algorithm for minimization with inequality constraints is known as Powell-Hestenes-Rockafellar (PHR) method. The main drawback of PHR is that the objective function of the subproblems is not twice continuously differentiable. This is the main motivation for the introduction of many alternative Augmented Lagrangian methods. Most of them have interesting interpretations as proximal point methods for solving the dual problem, when the original nonlinear programming problem is convex. In this paper a numerical comparison between many of these methods is performed using all the suitable problems of the CUTE collection.This author was supported by ProNEx MCT/CNPq/FAPERJ 171.164/2003, FAPESP (Grants 2001/04597-4 and 2002/00094-0 and 2003/09169-6) and CNPq (Grant 302266/2002-0).This author was partially supported by CNPq-Brasil and CDCHT-Venezuela.This author was supported by ProNEx MCT/CNPq/FAPERJ 171.164/2003, FAPESP (Grant 2001/04597-4) and CNPq.     

Suggested research topics in sensitivity and stability analysis for semi-infinite programming problems

We suggest several important research topics for semi-infinite programs whose problem functions and index sets contain parameters that are subject to perturbation. These include optimal value and optimal solution sensitivity and stability properties and penalty function approximation techniques. The approaches proposed are a natural carryover from parametric nonlinear programming, with emphasis on practical applicability and computability.Research supported by National Science Foundation Grant SES 8722504 and Grant ECS-86-19859 and Grant N00014-89-J-1537, Office of Naval Research.     

On heat kernel estimates and parabolic Harnack inequality for jump processes on metric measure spaces

In this paper, we discuss necessary and sufficient conditions on jumping kernels for a class of jump-type Markov processes on metric measure spaces to have scale-invariant finite range parabolic Harnack inequality.     

A second-order method for the general nonlinear programming problem

This paper presents a multiplier-type method for nonlinear programming problems with both equality and inequality constraints. Slack variables are used for the inequalities. The penalty coefficient is adjusted automatically, and the method converges quadratically to points satisfying second-order conditions.The work of the first author was supported by NSF RANN and JSEP Contract No. F44620-71-C-0087; the work of the second author was supported by the National Science Foundation Grant No. ENG73-08214A01 and US Army Research Office Durham Contract No. DAHC04-73-C-0025.     

The Fermat rule for multifunctions on Banach spaces

Using variational analysis, we study vector optimization problems with objectives being closed multifunctions on Banach spaces or in Asplund spaces. In particular, in terms of the coderivatives, we present Fermat’s rules as necessary conditions for an optimal solution of the above problems. As applications, we also provide some necessary conditions (in terms of Clarke’s normal cones or the limiting normal cones) for Pareto efficient points.This research was supported by a postdoctoral fellowship scheme (CUHK) and an Earmarked Grant from the Research Grant Council of Hong Kong. Research of the first author was also supported by the National Natural Science Foundation of P. R. China (Grant No. 10361008) and the Natural Science Foundation of Yunnan Province, P. R. China (Grant No. 2003A002M).     

Approximation Methods in Multiobjective Programming

Approaches to approximate the efficient set and Pareto set of multiobjective programs are reviewed. Special attention is given to approximating structures, methods generating Pareto points, and approximation quality. The survey covers more than 50 articles published since 1975.His work was supported by Deutsche Forschungsgemeinschaft, Grant HA 1795/7-2.Her work was done while on a sabbatical leave at the University of Kaiserslautern with support of Deutsche Forschungsgemeinschaft, Grant Ka 477/24-1.     

Necessary Conditions for Impulsive Nonlinear Optimal Control Problems without a priori Normality Assumptions

First-order and second-order necessary conditions of optimality for an impulsive control problem that remain informative for abnormal control processes are presented and derived. One of the main features of these conditions is that no a priori normality assumptions are required. This feature follows from the fact that these conditions rely on an extremal principle which is proved for an abstract minimization problem with equality constraints, inequality constraints, and constraints given by an inclusion in a convex cone. Two simple examples illustrate the power of the main result.The first author was partially supported by the Russian Foundation for Basic Research Grant 02-01-00334. The second author was partially supported by the Russian Foundation for Basic Research Grant 00-01-00869. The third author was partially supported by Fundacao para a Ciencia e Tecnologia and by INVOTAN Grant.     

Best simultaneous approximation to totally bounded sequences in Banach spaces

This paper is concerned with the problem of best weighted simultaneous approximations to totally bounded sequences in Banach spaces. Characterization results from convex sets in Banach spaces are established under the assumption that the Banach space is uniformly smooth. The first author is supported in part by Scientific Research Fund of Hunan Provincial Education Department (Grant No. 06C651); the second author is supported in part by the National Natural Science Foundation of China (Grant Nos. 10671175, 10731060) and Program for New Century Excellent Talents in University; the third author is supported in part by Projects MTM2006-13997-C02-01 and FQM-127 of Spain     

On real hypersurfaces with harmonic curvature of a quaternionic projective space

We classify certain real hypersurfaces of a quaternionic projective space satisfying some conditions on their Ricci tensors.Research partially supported by DGICYT Grant PS87-0115-C03-02     

On the solution of large,structured linear complementarity problems: The block partitioned case

This paper delineates the underlying theory of an efficient method for solving a class of specially-structured linear complementarity problems of potentially very large size. We propose a block-iterative method in which the subproblems are linear complementarity problems. Problems of the type considered here arise in the process of making discrete approximations to differential equations in the presence of special side conditions. This problem source is exemplified by the free boundary problem for finite-length journal bearings. Some of the authors' computational experience with the method is presented.Research partially supported by the Office of Naval Research under contract N-00014-67-A-0112-0011; U.S. Atomic Energy Commission Contract AT (04-3)-326 PA No. 18.Research partially supported by U.S. Atomic Energy Commission Contract AT(04-3)-326 PA No. 30; and National Science Foundation Grant GJ 35135X.     

Some Geometrical Aspects of Efficient Points in Vector Optimization

We study efficient point sets in terms of extreme points, positive support points and strongly positive exposed points. In the case when the ordering cone has a bounded base, we prove that the efficient point set of a weakly compact convex set is contained in the closed convex hull of its strongly positive exposed points, thereby extending the Phelps theorem. We study also the density of positive proper efficient point sets. This research was supported by a Central Research Grant of Hong Kong Polytechnic University, Grant G-T 507. Research of the first author was also supported by the National Natural Science Foundation of P.R. China, Grant 10361008, and the Natural Science Foundation of Yunnan Province, China, Grant 2003A002M. Research of the second author was also supported by the Natural Science Foundation of Chongqing. Research of the third author was supported by a research grant from Australian Research Counsil.