Multicriteria Planar Ordered Median Problems

In this paper, we deal with the determination of the entire set of Pareto solutions of location problems involving Q general criteria. These criteria include median, center, or centdian objective functions as particular instances. We characterize the set of Pareto solutions of all these multicriteria problems for any polyhedral gauge. An efficient algorithm is developed for the planar case and its complexity is established. Extensions to the nonconvex case are also considered. The proposed approach is more general than previously published approaches to multicriteria location problems.The research of the third and fourth authors was partially supported by Grants BFM2001-2378, BFM2001-4028, BFM2004-0909, and HA2003-0121.     

An approximate solution of linear multicriteria control problems through the multicriteria simplex method

This paper deals with multicriteria, linear, continuous optimal control problems through the application of the multicriteria simplex method. Since the system is linear, the state variables at a given time can be expressed in terms of definite integrals. Upon using standard numerical integration formulas, the definite integrals are approximately expressed by means of weighted sums of the integrands. Then, after introducing some suitable auxiliary variables, approximate linear multicriteria programming problems are formulated. Illustrative numerical examples are provided to indicate the efficiency of the proposed method.The author is indebted to Professor Y. Sawaragi of Kyoto University for his constant encouragement. The author also wishes to thank T. Suwa for his cooperation in preparing the programming for the digital computer.     

Thep-facility ordered median problem on networks

In this paper we deal with the ordered median problem: a family of location problems that allows us to deal with a large number of real situations which does not fit into the standard models of location analysis. Moreover, this family includes as particular instances many of the classical location models. Here, we analyze thep-facility version of this problem on networks and our goal is to study the structure of the set of candidate points to be optimal solutions. The research of the authors is partially financed by Spanish research grants BFM2001-2378, BFM2001-4028, BFM2004-0909 and HA2003-0121.     

Superlinear primal-dual affine scaling algorithms for LCP

We describe an interior-point algorithm for monotone linear complementarity problems in which primal-dual affine scaling is used to generate the search directions. The algorithm is shown to have global and superlinear convergence with Q-order up to (but not including) two. The technique is shown to be consistent with a potential-reduction algorithm, yielding the first potential-reduction algorithm that is both globally and superlinearly convergent.Corresponding author. The work of this author was based on research supported by the Office of Scientific Computing, U.S. Department of Energy, under Contract W-31-109-Eng-38.The work of this author was based on research supported by the National Science Foundation under grant DDM-9109404 and the Office of Naval Research under grant N00014-93-1-0234. This work was done while the author was a faculty member of the Systems and Industrial Engineering Department at the University of Arizona.     

Densities of One-Dimensional Backward SDEs

This work is devoted to the study of the existence and smoothness of the marginal densities of the solution of one-dimensional backward stochastic differential equations. Under monotonicity conditions of a function of the coefficients, we obtain that the smoothness properties of the forward process influencing the backward equation, transfer to the densities of the solution. Once established these conditions, we apply the result to study the tail behavior of the solution process. Mathematics Subject Classification (2000) 60H10.Fabio Antonelli: The first author was partially supported by the MIUR COFIN grant 2000.Arturo Kohatsu-Higa: The second author was partially supported by grants BFM2003-03324 and BFM 2003-04294. The authors wish to thank the referee for his/her comments.     

Generalized Maximin Solutions in Multicriteria Bargaining

In this paper we address bargaining games where the agents have to take into account different criteria to value the decisions. We propose the class of generalized maximin solutions, as the natural extension for these games of the maximin solutions in conventional bargaining. In order to refine this solution concept, we define a multicriteria lexicographic partial ordering and present the class of generalized leximin solutions as those that are nondominated with respect to this relation. We establish some properties of these solutions and characterize them as solutions of multicriteria problems. The research of the authors is partially supported by the Spanish Ministry of Science and Technology projects BFM2002-11282-E and BEC2003-03111.     

On Central-Path Proximity Measures in Interior-Point Methods

One of the main ingredients of interior-point methods is the generation of iterates in a neighborhood of the central path. Measuring how close the iterates are to the central path is an important aspect of such methods and it is accomplished by using proximity measure functions. In this paper, we propose a unified presentation of the proximity measures and a study of their relationships and computational role when using a generic primal-dual interior-point method for computing the analytic center for a standard linear optimization problem. We demonstrate that the choice of the proximity measure can affect greatly the performance of the method. It is shown that we may be able to choose the algorithmic parameters and the central-path neighborhood radius (size) in such a way to obtain comparable results for several measures. We discuss briefly how to relate some of these results to nonlinear programming problems. The first author was partially supported by Simón Bolívar University, Venezuelan National Council for Sciences and Technology (CONICIT) Grant PG97-000592, Center for Research on Parallel Computing of Rice University, and TU Delft. The authors thank Amr El Bakry, Richard Tapia, Adolfo Quiroz, and Pedro Berrizbeitia for discussions and suggestions. They acknowledge the observations and comments of the editors and an anonymous referee.     

On the convergence of primal-dual interior-point methods with wide neighborhoods

We study primal-dual interior-point methods for linear programs. After proposing a new primaldual potential function we describe a new potential reduction algorithm. We make connections between the new potential function and primal-dual interior-point algorithms with wide neighborhoods. Then we describe an algorithm that is a slightly modified version of existing primal-dual algorithms using wide neighborhoods. Assuming the optimal solution is non-degenerate, the algorithm is 1-step Q-quadratically convergent. We also study the degenerate case and show that the neighborhoods of the central path stay large as the iterates approach the optimal solutions.Research performed while the author was a Ph.D. student at Cornell University and was supported in part by the United States Army Research Office through the Army Center of Excellence for Symbolic Methods in Algorithmic Mathematics (ACSyAM), Mathematical Sciences Institute of Cornell University, Contract DAAL03-91-C-0027 and also by NSF, AFOSR and ONR through NSF Grant DMS-8920550.     

Superlinear and quadratic convergence of primal-dual interior-point methods for linear programming revisited

Recently, Zhang, Tapia, and Dennis (Ref. 1) produced a superlinear and quadratic convergence theory for the duality gap sequence in primal-dual interior-point methods for linear programming. In this theory, a basic assumption for superlinear convergence is the convergence of the iteration sequence; and a basic assumption for quadratic convergence is nondegeneracy. Several recent research projects have either used or built on this theory under one or both of the above-mentioned assumptions. In this paper, we remove both assumptions from the Zhang-Tapia-Dennis theory.Dedicated to the Memory of Magnus R. Hestenes, 1906–1991This research was supported in part by NSF Cooperative Agreement CCR-88-09615 and was initiated while the first author was at Rice University as a Visiting Member of the Center for Research in Parallel Computation.The authors thank Yinyu Ye for constructive comments and discussions concerning this material.This author was supported in part by NSF Grant DMS-91-02761 and DOE Grant DE-FG05-91-ER25100.This author was supported in part by AFOSR Grant 89-0363, DOE Grant DE-FG05-86-ER25017, and ARO Grant 9DAAL03-90-G-0093.     

Dimension filtration on loops

We show that the graded group associated to the dimension filtration on a loop acquires the structure of a Sabinin algebra after being tensored with a field of characteristic zero. The key to the proof is the interpretation of the primitive operations of Shestakov and Umirbaev in terms of the operations on a loop that measure the failure of the associator to be a homomorphism. The first author was partially supported by the CONACyT grant CO2-44100. The second author acknowledges support from BFM2001-3239-C03-02 (MCYT) and ANGI2001/26 (Plan Riojano de I+D).     

A parallel method for finding the global minimum of univariate functions

We describe a new parallel method for solving global optimization problems. The formulation of the decision rules of this method is presented. We examine convergence conditions of the proposed algorithm and establish conditions which guarantee a considerable speedup with respect to the sequential version of the algorithm. We also present some numerical experiments executed on Alliant FX/80 for one class of multiextremal functions.The authors are greatly indebted to R. G. Strongin who stimulated the fulfillment of this research. They also would like to thank the anonymous referees for their useful suggestions.The research of the first author was partially supported by Grant 9494/NC/89 from the Italian Government under the Italian-Soviet Agreement about the Cultural and Scientific Exchange in 1990–1991. He thanks the Systems Department, University of Calabria, where he was a Visitor.     

On the formulation and theory of the Newton interior-point method for nonlinear programming

In this work, we first study in detail the formulation of the primal-dual interior-point method for linear programming. We show that, contrary to popular belief, it cannot be viewed as a damped Newton method applied to the Karush-Kuhn-Tucker conditions for the logarithmic barrier function problem. Next, we extend the formulation to general nonlinear programming, and then validate this extension by demonstrating that this algorithm can be implemented so that it is locally and Q-quadratically convergent under only the standard Newton method assumptions. We also establish a global convergence theory for this algorithm and include promising numerical experimentation.The first two authors were supported in part by NSF Cooperative Agreement No. CCR-8809615, by Grants AFOSR 89-0363, DOE DEFG05-86ER25017, ARO 9DAAL03-90-G-0093, and the REDI Foundation. The fourth author was supported in part by NSF DMS-9102761 and DOE DE-FG02-93ER25171. The authors would like to thank Sandra Santos for painstakingly proofreading an earlier verion of this paper.     

Quadrilaterals and extremal quasiconformal extensions

We show that the smallest maximal dilatation for a quasiconformal extension of a quasisymmetric function of the unit circle may be larger than indicated by the change in the module of the quadrilaterals with vertices on the circle. The research of the second author has been partially supported by the Alfred P. Sloan Foundation and by the U.S. National Science Foundation grant DMS 94-00999. This research was completed while the first author was visiting the University of Illinois at Urbana-Champaign. He wishes to thank the Department of Mathematics for its kind hospitality.     

Primal-dual target-following algorithms for linear programming

In this paper, we propose a method for linear programming with the property that, starting from an initial non-central point, it generates iterates that simultaneously get closer to optimality and closer to centrality. The iterates follow paths that in the limit are tangential to the central path. Together with the convergence analysis, we provide a general framework which enables us to analyze various primal-dual algorithms in the literature in a short and uniform way.This work was completed with the support of a research grant from SHELL. The first author is supported by the Dutch Organization for Scientific Research (NWO), Grant No. 611-304-028. The third author is on leave from the Eötvös University, Budapest, and partially supported by OTKA No. 2116. The fourth author is supported by the Swiss National Foundation for Scientific Research, Grant No. 12-34002.92.     

A constructive proof of Ky Fan’s coincidence theorem

We present a constructive proof for the well-known Ky Fan’s coincidence theorem through a simplicial algorithm. In a finite number of steps the algorithm generates a simplex containing an approximate coincidence point. In the limit, when the mesh size converges to zero, the sequence of approximations converges to a coincidence point. This research was carried out while the second author was visiting the CentER for Economic Research, Tilburg University. He would like to thank both CentER and the Netherlands Organization for Scientific Research (NWO) for their financial support.     

Quasi-Modal Lattices

We introduce the class of bounded distributive lattices with two operators, Δ and ∇, the first between the lattice and the set of its ideals, and the second between the lattice and the set of its filters. The results presented can be understood as a generalization of the results obtained by S. Celani. Jorge Castro: The work of the first author was partially supported by Grant BFM2001-3329 of D.G.I.C.Y.T. of Spain.     

Bicriteria linear fractional programming

As a step toward the investigation of the multicriteria linear fractional program, this paper provides a thorough analysis of the bicriteria case. It is shown that the set of efficient points is a finite union of linearly constrained sets and the efficient frontier is the image of a finite number of connected line segments of efficient points. A simple algorithm using only one-dimensional parametric linear programming techniques is developed to evaluate the efficient frontier.This research was partially supported by NRC Research Grant No. A4743. The authors wish to thank two anonymous referees for their helpful comments on an earlier draft of this paper.     

Primal-dual row-action method for convex programming

We present a primal-dual row-action method for the minimization of a convex function subject to general convex constraints. Constraints are used one at a time, no changes are made in the constraint functions and their Jacobian matrix (thus, the row-action nature of the algorithm), and at each iteration a subproblem is solved consisting of minimization of the objective function subject to one or two linear equations. The algorithm generates two sequences: one of them, called primal, converges to the solution of the problem; the other one, called dual, approximates a vector of optimal KKT multipliers for the problem. We prove convergence of the primal sequence for general convex constraints. In the case of linear constraints, we prove that the primal sequence converges at least linearly and obtain as a consequence the convergence of the dual sequence.The research of the first author was partially supported by CNPq Grant No. 301280/86.     

Weighted norm inequalities for maximally modulated singular integral operators

We present a framework that yields a variety of weighted and vector-valued estimates for maximally modulated Calderón-Zygmund singular (and maximal singular) integrals from a single a priori weak type unweighted estimate for the maximal modulations of such operators. We discuss two approaches, one based on the good- method of Coifman and Fefferman [CF] and an alternative method employing the sharp maximal operator. As an application we obtain new weighted and vector-valued inequalities for the Carleson operator proving that it is controlled by a natural maximal function associated with the Orlicz space L(log L)(log log log L). This control is in the sense of a good- inequality and yields strong and weak type estimates as well as vector-valued and weighted estimates for the operator in question.Mathematics Subject Classification (2000): 42B20, 42B25The first author is supported by the National Science Foundation under grant DMS 0099881.Part of this work was carried out while the second author was a Postdoctoral Fellow at University of Missouri-Columbia. The second author would like to thank this department for its support and hospitality.The second and the third authors are partially supported by MCYT Grant BFM2001-0189.