7,389 research outputs found
A Probability-one Homotopy Algoithm for Non-Smooth Equations and Mixed Complementarity Problems
A probability-one homotopy algorithm for solving nonsmooth equations is described. This algorithm is able to solve problems involving highly nonlinear equations,where the norm of the residual has non-global local minima.The algorithm is based on constructing homotopy mappings that are smooth in the interior of their domains.The algorithm is specialized to solve mixed complementarity problems through the use of MCP functions and associated smoothers.This specialized algorithm includes an option to ensure that all iterates remain feasible.Easily satisfiable sufficient conditions are given to ensure that the homotopy zero curve remains feasible,and global convergence properties for the MCP algorithm are developed.Computational results on the MCPLIB test library demonstrate the effectiveness of the algorithm
Deflation for semismooth equations
Variational inequalities can in general support distinct solutions. In this
paper we study an algorithm for computing distinct solutions of a variational
inequality, without varying the initial guess supplied to the solver. The
central idea is the combination of a semismooth Newton method with a deflation
operator that eliminates known solutions from consideration. Given one root of
a semismooth residual, deflation constructs a new problem for which a
semismooth Newton method will not converge to the known root, even from the
same initial guess. This enables the discovery of other roots. We prove the
effectiveness of the deflation technique under the same assumptions that
guarantee locally superlinear convergence of a semismooth Newton method. We
demonstrate its utility on various finite- and infinite-dimensional examples
drawn from constrained optimization, game theory, economics and solid
mechanics.Comment: 24 pages, 3 figure
Linear complementarity problems on extended second order cones
In this paper, we study the linear complementarity problems on extended
second order cones. We convert a linear complementarity problem on an extended
second order cone into a mixed complementarity problem on the non-negative
orthant. We state necessary and sufficient conditions for a point to be a
solution of the converted problem. We also present solution strategies for this
problem, such as the Newton method and Levenberg-Marquardt algorithm. Finally,
we present some numerical examples
Gas phase appearance and disappearance as a problem with complementarity constraints
The modeling of migration of hydrogen produced by the corrosion of the
nuclear waste packages in an underground storage including the dissolution of
hydrogen involves a set of nonlinear partial differential equations with
nonlinear complementarity constraints. This article shows how to apply a modern
and efficient solution strategy, the Newton-min method, to this geoscience
problem and investigates its applicability and efficiency. In particular,
numerical experiments show that the Newton-min method is quadratically
convergent for this problem.Comment: Accepted for Publication in Mathematics and Computers in Simulation.
Available online 6 August 2013, Mathematics and Computers in Simulation
(2013
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Reformulations of mathematical programming problems as linear complementarity problems
A family of complementarity problems are defined as extensions of the well known Linear Complementarity Problem (LCP). These are
(i.) Second Linear Complementarity Problem (SLCP) which is an LCP extended by introducing further equality restrictions and unrestricted variables,
(ii.) Minimum Linear Complementarity Problem (MLCP) which is an
LCP with additional variables not required to be complementary and with a linear objective function which is to be minimized,
(iii.) Second Minimum Linear Complementarity Problem (SMLCP) which is an MLCP but the nonnegative restriction on one of each pair of complementary variables is relaxed so that it is allowed to be unrestricted in value.
A number of well known mathematical programming problems, namely quadratic programming (convex, nonconvex, pseudoconvex nonconvex), bilinear programming, game theory, zero-one integer programming, the fixed charge problem, absolute value programming, variable separable programming are reformulated as members of this family of four complementarity problems
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