QPECgen, a MATLAB Generator for Mathematical Programs with Quadratic Objectives and Affine Variational Inequality Constraints

نویسندگان

  • Houyuan Jiang
  • Daniel Ralph
چکیده

We describe a technique for generating a special class, called QPEC, of mathematical programs with equilibrium constraints, MPEC. A QPEC is a quadratic MPEC, that is an optimization problem whose objective function is quadratic, first-level constraints are linear, and second-level (equilibrium) constraints are given by a parametric affine variational inequality or one of its specialisations. The generator, written in MATLAB, allows the user to control different properties of the QPEC and its solution. Options include the proportion of degenerate constraints in both the first and second level, ill-conditioning, convexity of the objective, monotonicity and symmetry of the second-level problem, and so on. We believe these properties may substantially effect efficiency of existing methods for MPEC, and illustrate this numerically by applying several methods to generator test problems.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

{37 () Qpecgen, a Matlab Generator for Mathematical Programs with Quadratic Objectives and Aane Variational Inequality Constraints

We describe a technique for generating a special class, called QPEC, of mathematical programs with equilibrium constraints, MPEC. A QPEC is a quadratic MPEC, that is an optimization problem whose objective function is quadratic, rst-level constraints are linear, and second-level (equilibrium) constraints are given by a parametric aane variational inequality or one of its specialisations. The ge...

متن کامل

MATLAB Simulink modeling and simulation of LVI-based primal-dual neural network for solving linear and quadratic programs

In view of parallel-processing nature and circuit-implementation convenience, recurrent neural networks are often employed to solve optimization problems. Recently, a primal-dual neural network based on linear variational inequalities (LVI) was developed by Zhang et al. for the online solution of linear-programming (LP) and quadratic-programming (QP) problems simultaneously subject to equality,...

متن کامل

Technical Report EE04025 - Notes on Linear Model Predictive Control

Linear model predictive control (MPC) assumes a linear system model, that the constraints sets are representable via linear inequalities and that the objective function is convex quadratic. Linear MPC is appealing because the associated optimisation problem typically solved at each time interval may be expressed as a convex quadratic program, which can be solved efficiently online. Topics not c...

متن کامل

Further Applications of a Splitting Algorithm to Decomposition in Variational Inequalities and Convex Programming

A classical method for solving the variational inequality problem is the projection algorithm. We show that existing convergence results for this algorithm follow from one given by Gabay for a splitting algorithm for finding a zero of the sum of two maximal monotone operators. Moreover, we extend the projection algorithm to solve any monotone affine variational inequality problem. When applied ...

متن کامل

Optimality Conditions for Optimization Problems with Complementarity Constraints

Optimization problems with complementarity constraints are closely related to optimization problems with variational inequality constraints and bilevel programming problems. In this paper, under mild constraint qualifications, we derive some necessary and sufficient optimality conditions involving the proximal coderivatives. As an illustration of applications, the result is applied to the bilev...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Comp. Opt. and Appl.

دوره 13  شماره 

صفحات  -

تاریخ انتشار 1999