Sample-path optimization of convex stochastic performance functions

In this paper we propose a method for optimizing convex performance functions in stochastic systems. These functions can include expected performance in static systems and steady-state performance in discrete-event dynamic systems; they may be nonsmooth. The method is closely related to retrospective simulation optimization; it appears to overcome some limitations of stochastic approximation, which is often applied to such problems. We explain the method and give computational results for two classes of problems: tandem production lines with up to 50 machines, and stochastic PERT (Program Evaluation and Review Technique) problems with up to 70 nodes and 110 arcs. Sponsored by the National Science Foundation under grant number CCR-9109345, by the Air Force Systems Command, USAF, under grant numbers F49620-93-1-0068 and F49620-95-1-0222, by the U.S. Army Research Office under grant number DAAL03-92-G-0408, and by the U.S. Army Space and Strategic Defense Command under contract number DASG60-91-C-0144. The U.S. Government has certain rights in this material, and is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. Sponsored by a Wisconsin/Hilldale Research Award, by the U.S. Army Space and Strategic Defense Command under contract number DASG60-91-C-0144, and the Air Force Systems Command, USAF, under grant number F49620-93-1-0068. Sponsored by the National Science Foundation under grant number DDM-9201813.     

A reduction method for variational inequalities

This paper explains a method by which the number of variables in a variational inequality having a certain form can be substantially reduced by changing the set over which the variational inequality is posed. The method applies in particular to certain economic equilibrium problems occurring in applications. We explain and justify the method, and give examples of its application, including a numerical example in which the solution time for the reduced problem was approximately 2% of that for the problem in its original form. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.The research reported here was sponsored by the Air Force Office of Scientific Research, Air Force Materiel Command, USAF, under grant number F49620-95-1-0222, and by the U.S. Army Research Office under grant number DAAH04-95-1-0149. The U.S. Government has certain rights in this material, and is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the sponsoring agencies or the U.S. Government.     

Wachspress type rational complex planar splines of degree (3,1)

We study the existence, uniqueness and approximation properties of rational complex planar spline interpolants of order (3, 1). We also find sufficient conditions for such interpolants to be quasiregular and quasiconformal. Examples are given. This work was carried out with the aid of MACSYMA, a large symbolic manipulation program developed at the MIT Laboratory for Computer Science and supported from 1975 to 1983 by the National Aeronautics and Space Administration under grant NSG 1323, by the Office of Naval Research under grant N00014-77C-0641, by the U.S. Department of Energy under grant ET-78-C-024687, and by the U.S. Air Force under grant F49620-79-C-020, and since 1982 by Symbolics, Inc. of Burlington, MA.     

Newton's method for a class of nonsmooth functions

This paper presents and justifies a Newton iterative process for finding zeros of functions admitting a certain type of approximation. This class includes smooth functions as well as nonsmooth reformulations of variational inequalities. We prove for this method an analogue of the fundamental local convergence theorem of Kantorovich including optimal error bounds.The research reported here was sponsored by the National Science Foundation under Grants CCR-8801489 and CCR-9109345, by the Air Force Systems Command, USAF, under Grants AFOSR-88-0090 and F49620-93-1-0068, by the U. S. Army Research Office under Grant No. DAAL03-92-G-0408, and by the U. S. Army Space and Strategic Defense Command under Contract No. DASG60-91-C-0144. The U. S. Government has certain rights in this material, and is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.     

Strong law for mixing sequence

In this article we present some theorems on the strong law for the mixing sequence which is not necessarily stationary, with the mixing coefficient involving only a pair of variables in the sequence.Research sponsored by the Air Force Office of Scientific Research under Contract F 49620-85-C-0008. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.This author is also supported by National Natural Science Foundation of China.     

Optimization with unary functions

Most nonlinear programming problems consist of functions which are sums of unary functions of linear functions. Advantage can be taken of this form to calculate second and higher order derivatives easily and at little cost. Using these, high order optimization techniques such as Halley's method can be utilized to accelerate the rate of convergence to the solution. These higher order derivatives can also be used to compute second order sensitivity information. These techniques are applied to the solution of the classical chemical equilibrium problem.Supported by National Science Foundation grant ECS-8709795, co-funded by the U.S. Air Force Office of Scientific Research and by the Office of Naval Research grant N00014-86-K0052.Supported by National Science Foundation grant ECS-8709795, co-funded by the U.S. Air Force Office of Scientific Research.     

On the pricing of American options

The problem of valuation for contingent claims that can be exercised at any time before or at maturity, such as American options, is discussed in the manner of Bensoussan [1]. We offer an approach which both simplifies and extends the results of existing theory on this topic.Research supported in part by the National Science Foundation under Grant No. NSF-DMS-84-16736 and by the Air Force Office of Scientific Research under Grant No. F49620-85-C-0144.     

On the convergence of Newton iterations to non-stationary points

We study conditions under which line search Newton methods for nonlinear systems of equations and optimization fail due to the presence of singular non-stationary points. These points are not solutions of the problem and are characterized by the fact that Jacobian or Hessian matrices are singular. It is shown that, for systems of nonlinear equations, the interaction between the Newton direction and the merit function can prevent the iterates from escaping such non-stationary points. The unconstrained minimization problem is also studied, and conditions under which false convergence cannot occur are presented. Several examples illustrating failure of Newton iterations for constrained optimization are also presented. The paper also shows that a class of line search feasible interior methods cannot exhibit convergence to non-stationary points. This author was supported by Air Force Office of Scientific Research grant F49620-00-1-0162, Army Research Office Grant DAAG55-98-1-0176, and National Science Foundation grant INT-9726199.This author was supported by Department of Energy grant DE-FG02-87ER25047-A004.This author was supported by National Science Foundation grant CCR-9987818 and Department of Energy grant DE-FG02-87ER25047-A004.     

The Skorohod integral and the derivative operator of functional of a cylindrical Brownian motion

The paper presents a definition of the Skorohod integral of operator-valued processes and the derivative operator for functional of a cylindrical Brownian motionW on a Hilbert space. The method is based on the chaos expansions in terms of multiple Wiener integrals ofW.This research was partially supported by the U.S. Air Force Office of Scientific Research Contract No. F49620 85C 0144. The research of V. Pérez-Abreu was also supported by CONACYT Grant D111-904237.     

On the limit of the largest eigenvalue of the large dimensional sample covariance matrix

Summary In this paper the authors show that the largest eigenvalue of the sample covariance matrix tends to a limit under certain conditions when both the number of variables and the sample size tend to infinity. The above result is proved under the mild restriction that the fourth moment of the elements of the sample sums of squares and cross products (SP) matrix exist.Research sponsored by the Air Force Office of Scientific Research under Contract F49620-C-0008. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereonThe work of this author was done when he was working at the Center for Multivariate Analysis, University of Pittsburgh.