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47
An overview of bilevel optimization
, 2007
"... This paper is devoted to bilevel optimization, a branch of mathematical programming of both practical and theoretical interest. Starting with a simple example, we proceed towards a general formulation. We then present fields of application, focus on solution approaches, and make the connection wit ..."
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Cited by 68 (3 self)
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This paper is devoted to bilevel optimization, a branch of mathematical programming of both practical and theoretical interest. Starting with a simple example, we proceed towards a general formulation. We then present fields of application, focus on solution approaches, and make the connection with MPECs (Mathematical Programs with Equilibrium Constraints).
SOLVING MATHEMATICAL PROGRAMS WITH COMPLEMENTARITY CONSTRAINTS AS NONLINEAR PROGRAMS
 OPTIM. METHODS SOFTW. 19, 1540
, 2004
"... ..."
Stochastic mathematical programs with equilibrium constraints, modeling and . . .
 SCHOOL OF INDUSTRIAL AND SYSTEM ENGINEERING, GEORGIA INSTITUTE OF TECHNOLOGY
, 2005
"... In this paper, we discuss the sample average approximation (SAA) method applied to a class of stochastic mathematical programs with variational (equilibrium) constraints. To this end, we briefly investigate the structure of both – the lower level equilibrium solution and objective integrand. We sho ..."
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Cited by 35 (7 self)
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In this paper, we discuss the sample average approximation (SAA) method applied to a class of stochastic mathematical programs with variational (equilibrium) constraints. To this end, we briefly investigate the structure of both – the lower level equilibrium solution and objective integrand. We show almost sure convergence of optimal values, optimal solutions (both local and global) and generalized KarushKuhnTucker points of the SAA program to their true counterparts. We also study uniform exponential convergence of the sample average approximations, and as a consequence derive estimates of the sample size required to solve the true problem with a given accuracy. Finally we present some preliminary numerical test results.
An implementable activeset algorithm for computing a Bstationary point of a mathematical program with linear complementarity constraints
 SIAM J. Optim
"... Abstract. In [3], an ɛactive set algorithm was proposed for solving a mathematical program with a smooth objective function and linear inequality/complementarity constraints. It is asserted therein that, under a uniform LICQ on the ɛfeasible set, this algorithm generates iterates whose cluster poi ..."
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Cited by 30 (4 self)
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Abstract. In [3], an ɛactive set algorithm was proposed for solving a mathematical program with a smooth objective function and linear inequality/complementarity constraints. It is asserted therein that, under a uniform LICQ on the ɛfeasible set, this algorithm generates iterates whose cluster points are Bstationary points of the problem. However, the proof has a gap and only shows that each cluster point is an Mstationary point. We discuss this gap and show that Bstationarity can be achieved if the algorithm is modified and an additional error bound condition holds. Key words. MPEC, Bstationary point, ɛactive set, error bound AMS subject classifications. 65K05, 90C30, 90C33
An interior point method for mathematical programs with complementarity constraints (MPCCs)
 SIAM JOURNAL ON OPTIMIZATION
, 2003
"... Interior point methods for nonlinear programs (NLP) are adapted for solution of mathematical programs with complementarity constraints (MPCCs). The constraints of the MPCC are suitably relaxed so as to guarantee a strictly feasible interior for the inequality constraints. The standard primaldual ..."
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Cited by 24 (1 self)
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Interior point methods for nonlinear programs (NLP) are adapted for solution of mathematical programs with complementarity constraints (MPCCs). The constraints of the MPCC are suitably relaxed so as to guarantee a strictly feasible interior for the inequality constraints. The standard primaldual algorithm has been adapted with a modified step calculation. The algorithm is shown to be superlinearly convergent in the neighborhood of the solution set under assumptions of MPCCLICQ, strong stationarity and upper level strict complementarity. The modification can be easily accommodated within most nonlinear programming interior point algorithms with identical local behavior. Numerical experience is also presented and holds promise for the proposed method.
Numerical experience with solving MPECs as NLPs
 Department of Mathematics and Computer Science, University of Dundee, Dundee
, 2002
"... This paper describes numerical experience with solving MPECs as NLPs on a large collection of test problems. The key idea is to use offtheshelf NLP solvers to tackle large instances of MPECs. It is shown that SQP methods are very well suited to solving MPECs and at present outperform Interior Poin ..."
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Cited by 22 (1 self)
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This paper describes numerical experience with solving MPECs as NLPs on a large collection of test problems. The key idea is to use offtheshelf NLP solvers to tackle large instances of MPECs. It is shown that SQP methods are very well suited to solving MPECs and at present outperform Interior Point solvers both in terms of speed and reliability. All NLP solvers also compare very favourably to special MPEC solvers on tests published in the literature.
On the Global Solution of Linear Programs with Linear Complementarity Constraints
, 2007
"... This paper presents a parameterfree integerprogramming based algorithm for the global resolution of a linear program with linear complementarity constraints (LPEC). The cornerstone of the algorithm is a minimax integer program formulation that characterizes and provides certificates for the three ..."
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Cited by 20 (3 self)
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This paper presents a parameterfree integerprogramming based algorithm for the global resolution of a linear program with linear complementarity constraints (LPEC). The cornerstone of the algorithm is a minimax integer program formulation that characterizes and provides certificates for the three outcomes—infeasibility, unboundedness, or solvability—of an LPEC. An extreme point/ray generation scheme in the spirit of Benders decomposition is developed, from which valid inequalities in the form of satisfiability constraints are obtained. The feasibility problem of these inequalities and the carefully guided linear programming relaxations of the LPEC are the workhorse of the algorithm, which also employs a specialized procedure for the sparsification of the satifiability cuts. We establish the finite termination of the algorithm and report computational results using the algorithm for solving randomly generated LPECs of reasonable sizes. The results establish that the algorithm can handle infeasible, unbounded, and solvable LPECs effectively.
Complementarity And Related Problems: A Survey
, 1998
"... This survey gives an introduction to some of the recent developments in the field of complementarity and related problems. After presenting two typical examples and the basic existence and uniqueness results, we focus on some new trends for solving nonlinear complementarity problems. Extensions to ..."
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Cited by 18 (0 self)
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This survey gives an introduction to some of the recent developments in the field of complementarity and related problems. After presenting two typical examples and the basic existence and uniqueness results, we focus on some new trends for solving nonlinear complementarity problems. Extensions to mixed complementarity problems, variational inequalities and mathematical programs with equilibrium constraints are also discussed.
Solving stochastic mathematical programs with equilibrium constraints via approximation and smoothing implicit programming with penalization
"... Abstract In this paper, we consider the stochastic mathematical programs with equilibrium constraints, which includes two kinds of models called hereandnow and lowerlevel waitandsee problems. We present a combined smoothing implicit programming and penalty method for the problems with a finite ..."
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Cited by 17 (8 self)
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Abstract In this paper, we consider the stochastic mathematical programs with equilibrium constraints, which includes two kinds of models called hereandnow and lowerlevel waitandsee problems. We present a combined smoothing implicit programming and penalty method for the problems with a finite sample space. Then, we suggest a quasiMonte Carlo approximation method for solving a problem with continuous random variables. A comprehensive convergence theory is included as well. We further report numerical results with the socalled picnic vender decision problem. Key words. Stochastic mathematical program with equilibrium constraints, waitandsee, hereandnow, smoothing implicit programming, penalty method, quasiMonte Carlo method. 1
THE THEORY OF 2REGULARITY FOR MAPPINGS WITH LIPSCHITZIAN DERIVATIVES AND ITS APPLICATIONS TO OPTIMALITY CONDITIONS
, 2002
"... We study local structure of a nonlinear mapping near points where standard regularity and/or smoothness assumptions need not be satisfied. We introduce a new concept of 2regularity (a certain kind of secondorder regularity) for a once differentiable mapping whose derivative is Lipschitz continuous ..."
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Cited by 17 (14 self)
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We study local structure of a nonlinear mapping near points where standard regularity and/or smoothness assumptions need not be satisfied. We introduce a new concept of 2regularity (a certain kind of secondorder regularity) for a once differentiable mapping whose derivative is Lipschitz continuous. Under this 2regularity condition, we obtain the representation theorem and the covering theorem (i.e., stability with respect to “righthand side ” perturbations) under assumptions that are weaker than those previously employed in the literature for results of this type. These results are further used to derive a constructive description of the tangent cone to a set defined by (2regular) equality constraints and optimality conditions for related optimization problems. The class of mappings introduced and studied in the paper appears to be a convenient tool for treating complementarity structures by means of an appropriate equationbased reformulation. Optimality conditions for mathematical programs with (equivalently reformulated) complementarity constraints are also discussed.