Combining the regularization strategy and the SQP to solve MPCC - A MATLAB implementation

نویسندگان

  • M. Teresa T. Monteiro
  • Helena Sofia Rodrigues
چکیده

Mathematical Program with Complementarity Constraints (MPCC) plays a very important role in many fields such as engineering design, economic equilibrium, multilevel game, and mathematical programming theory itself. In theory its constraints fail to satisfy a standard constraint qualification such as the linear independence constraint qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ) at any feasible point. As a result, the developed nonlinear programming theory may not be applied to MPCC class directly. Nowadays, a natural and popular approach is try to find some suitable approximations of an MPCC so that it can be solved by solving a sequence of nonlinear programs. This work aims to solve the MPCC using nonlinear programming techniques, namely the SQP and the regularization scheme. Some algorithms with two iterative processes, the inner and the external, were developed. A set of AMPL problems from MacMPEC database [7] were tested. The algorithms performance comparative analysis was carried out.

برای دانلود رایگان 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

A penalty method and a regularization strategy to solve MPCC

The goal of this paper is to solve Mathematical Program with Complementarity Constraints (MPCC) using nonlinear programming (NLP) techniques. This work presents two algorithms based on several nonlinear techniques such as Sequential Quadratic Programming (SQP), penalty techniques and regularization schemes. A set of AMPL problems were tested and the computational experience shows that both algo...

متن کامل

An inexact alternating direction method with SQP regularization for the structured variational inequalities

In this paper, we propose an inexact alternating direction method with square quadratic proximal  (SQP) regularization for  the structured variational inequalities. The predictor is obtained via solving SQP system  approximately  under significantly  relaxed accuracy criterion  and the new iterate is computed directly by an explicit formula derived from the original SQP method. Under appropriat...

متن کامل

Solving Mathematical Programs with Complementarity Constraints with Nonlinear Solvers

S u m m a r y. MPCC can be solved with specific MPCC codes or in its nonlinear equivalent formulation (NLP) using NLP solvers. Two NLP solvers-NPSOL and the line search filter SQP-are used to solve a collection of test problems in AMPL. Both are based on SQP (Sequential Quadratic Programming) philosophy but the second one uses a line search filter scheme.

متن کامل

Using Modified IPSO-SQP Algorithm to Solve Nonlinear Time Optimal Bang-Bang Control Problem

In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

متن کامل

An Active-Set Newton Method for Mathematical Programs with Complementarity Constraints

For a mathematical program with complementarity constraints (MPCC), we propose an active-set Newton method, which has the property of local quadratic convergence under the MPCC linear independence constraint qualification (MPCC-LICQ) and the standard second-order sufficient condition (SOSC) for optimality. Under MPCC-LICQ, this SOSC is equivalent to the piecewise SOSC on branches of MPCC, which...

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

عنوان ژورنال:
  • J. Computational Applied Mathematics

دوره 235  شماره 

صفحات  -

تاریخ انتشار 2011