Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Mathematical Programming: Series A and B
Hierarchical optimization: an introduction
Annals of Operations Research - Special issue on hierarchical optimization
Generating quadratic bilevel programming test problems
ACM Transactions on Mathematical Software (TOMS)
Descent approaches for quadratic bilevel programming
Journal of Optimization Theory and Applications
A numerical approach to optimization problems with variational inequality constraints
Mathematical Programming: Series A and B
On bilevel programming, part I: general nonlinear cases
Mathematical Programming: Series A and B
Exact penalization and stationarity conditions of mathematical programs with equilibrium constraints
Mathematical Programming: Series A and B
Computational Optimization and Applications
Some Feasibility Issues in Mathematical Programs with Equilibrium Constraints
SIAM Journal on Optimization
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Extension of Quasi-Newton Methods to Mathematical Programs with Complementarity Constraints
Computational Optimization and Applications
Computational Optimization and Applications
A Robust SQP Method for Mathematical Programs with Linear Complementarity Constraints
Computational Optimization and Applications
Newton-Type method for a class of mathematical programs with complementarity constraints
Computers & Mathematics with Applications
The C-Index: A New Stability Concept for Quadratic Programs with Complementarity Constraints
Mathematics of Operations Research
On convex quadratic programs with linear complementarity constraints
Computational Optimization and Applications
| Hi-index | 0.00 |
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 problemwhose objective function is quadratic, first-level constraints arelinear, and second-level (equilibrium) constraints are given by aparametric affine variational inequality or one of itsspecialisations. The generator, written in MATLAB, allows the user tocontrol different properties of the QPEC and its solution. Optionsinclude the proportion of degenerate constraints in both the firstand second level, ill-conditioning, convexity of the objective,monotonicity and symmetry of the second-level problem, and so on. Webelieve these properties may substantially effect efficiency ofexisting methods for MPEC, and illustrate this numerically byapplying several methods to generator test problems. Documentationand relevant codes can be found by visiting http://www.ms.unimelb.edu.au/∼danny/qpecgendoc.html.