Frailty is defined as an age-related decline in physiological reserve and increased vulnerability to stress. As frailty a multifaceted condition, there no effective pharmacotherapy for it yet. Ninjin’yoeito (NYT) Kamikihito (KKT), traditional Japanese medicines (Kampo medicines), are promising treating conditions of including fatigue mental anxiety. However, their effects still unclear. In this...

A popular technique of designing multiple-input multiple-output (MIMO) communication systems relies on optimizing the positive semidefinite covariance matrix at source. In this paper, a unified MIMO optimization framework based Karush-Kuhn-Tucker (KKT) conditions is proposed. framework, with aid theory, <xref ref-type="theorem" rid="theorem1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns...

K e y w o r d s M u l t i o b j e c t i v e optimization, Mangasarian-l'~romovitz type conditions, Second-order optimality conditions. 1. I N T R O D U C T I O N We consider the following constrained multiobjective program: min f(x), subject to x E X, (1) int R~ where the feasible region is described by inequalities and equalities X := {x • R": g(x) <_ O, h(x) = 0}, with f : R" ---* R t, g : R ...

Multistage stochastic optimization leads to NLPs over scenario trees that become extremely large when many time stages or fine discretizations of the probability space are required. Interior-point methods are well suited for these problems if the arising huge, structured KKT systems can be solved efficiently, for instance, with a large scenario tree but a moderate number of variables per node. ...

The bilevel program is a sequence of two optimization problems where the constraint region of the upper level problem is determined implicitly by the solution set to the lower level problem. The classical approach to solving such a problem is to replace the lower level problem by its Karush–Kuhn–Tucker (KKT) condition and solve the resulting mathematical programming problem with equilibrium con...

This paper presents a branch-and-bound algorithm for nonconvex quadratic programming, which is based on solving semidefinite relaxations at each node of the enumeration tree. The method is motivated by a recent branch-and-cut approach for the box-constrained case that employs linear relaxations of the first-order KKT conditions. We discuss certain limitations of linear relaxations when handling...

Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for the parallel numerical solution of such problems involve sequential quadratic programming (SQP), with either reduced or full space approaches. In this paper we propose and investigate a class of parallel full space SQP Lagrange...

Multiple Modular Design (MMD) is the method of designing a set of standard modules to meet demands for di erent functions. This work aims to nd an optimal set of modules given the demands. In this paper, we start with Evans' nonlinear programming model of MMD. By exploring the special structure of the formulation, we develop several properties of optimal solutions. With these properties, we dev...