Numerical validation of solutions of linear complementarity problems

Summary. This paper proposes a validation method for solutions of linear complementarity problems. The validation procedure consists of two sufficient conditions that can be tested on a digital computer. If the first condition is satisfied then a given multidimensional interval centered at an approximate solution of the problem is guaranteed to contain an exact solution. If the second condition is satisfied then the multidimensional interval is guaranteed to contain no exact solution. This study is based on the mean value theorem for absolutely continuous functions and the reformulation of linear complementarity problems as nonsmooth nonlinear systems of equations. Received August 21, 1997 / Revised version July 2, 1998     

Line search termination criteria for collinear scaling algorithms for minimizing a class of convex functions

Summary. Many successful quasi-Newton methods for optimization are based on positive definite local quadratic approximations to the objective function that interpolate the values of the gradient at the current and new iterates. Line search termination criteria used in such quasi-Newton methods usually possess two important properties. First, they guarantee the existence of such a local quadratic approximation. Second, under suitable conditions, they allow one to prove that the limit of the component of the gradient in the normalized search direction is zero. This is usually an intermediate result in proving convergence. Collinear scaling algorithms proposed initially by Davidon in 1980 are natural extensions of quasi-Newton methods in the sense that they are based on normal conic local approximations that extend positive definite local quadratic approximations, and that they interpolate values of both the gradient and the function at the current and new iterates. Line search termination criteria that guarantee the existence of such a normal conic local approximation, which also allow one to prove that the component of the gradient in the normalized search direction tends to zero, are not known. In this paper, we propose such line search termination criteria for an important special case where the function being minimized belongs to a certain class of convex functions. Received February 1, 1997 / Revised version received September 8, 1997     

Stability of Runge-Kutta methods for linear delay differential equations

Summary. This paper investigates the stability of Runge-Kutta methods when they are applied to the complex linear scalar delay differential equation . This kind of stability is called stability. We give a characterization of stable Runge-Kutta methods and then we prove that implicit Euler method is stable. Received November 3, 1998 / Revised version received March 23, 1999 / Published online July 12, 2000     

Improved smoothing-type methods for the solution of linear programs

Summary. We consider a smoothing-type method for the solution of linear programs. Its main idea is to reformulate the primal-dual optimality conditions as a nonlinear and nonsmooth system of equations, and to apply a Newton-type method to a smooth approximation of this nonsmooth system. The method presented here is a predictor-corrector method, and is closely related to some methods recently proposed by Burke and Xu on the one hand, and by the authors on the other hand. However, here we state stronger global and/or local convergence properties. Moreover, we present quite promising numerical results for the whole netlib test problem collection. Received August 9, 2000 / Revised version received September 28, 2000 / Published online June 7, 2001     

A Cholesky dual method for proximal piecewise linear programming

Summary. A quadratic programming method is given for minimizing a sum of piecewise linear functions and a proximal quadratic term, subject to simple bounds on variables. It may be used for search direction finding in nondifferentiable optimization algorithms. An efficient implementation is described that updates a Cholesky factorization of active constraints and provides good accuracy via iterative refinement. Numerical experience is reported for some large problems. Received March 29, 1993 / Revised version received December 18, 1993     

A new line-search step based on the Weierstrass \wp-function for minimizing a class of logarithmic barrier functions

Summary. We define the notion of self-concordance of order two for the restriction of a logarithmic barrier function to a given line. Based on this notion we prove an inner approximation of the domain of , as well as a lower bound of the distance from a point $t$ to the minimum of . These results provide the theoretical tools to develop a simple and efficient search step for finding the minimum of the barrier function along a given line. The new bound on the size of the line-search step is better than the optimal bound known for the case of a self-concordant function (of order one). We conclude with some numerical examples that illustrate the promise of the new line-search step. Received May 24, 1993 / Revised version received February 1994     

Numerical solution of constant coefficient linear delay differential equations as abstract Cauchy problems

Summary. In this paper we present an approach for the numerical solution of delay differential equations where , and , different from the classical step-by-step method. We restate (1) as an abstract Cauchy problem and then we discretize it in a system of ordinary differential equations. The scheme of discretization is proved to be convergent. Moreover the asymptotic stability is investigated for two significant classes of asymptotically stable problems (1). Received May 4, 1998 / Revised version received January 25, 1999 / Published online November 17, 1999     

On the analyticity properties of infeasible-interior-point paths for monotone linear complementarity problems

Infeasible-interior-point paths , a positive vector, for a horizontal linear complementarity problem are defined as the solution of () If the path converges for , then it converges to a solution of . This paper deals with the analyticity properties of and its derivatives with respect to r near r = 0 for solvable monotone complementarity problems . It is shown for with a strictly complementary solution that the path , , has an extension to which is analytic also at . If has no strictly complementary solution, then , , has an extension to that is analytic at . Received May 24, 1996 / Revised version received February 25, 1998     

A polyhedral approach to multicommodity survivable network design

Summary. The design of cost-efficient networks satisfying certain survivability constraints is of major concern to the telecommunications industry. In this paper we study a problem of extending the capacity of a network by discrete steps as cheaply as possible, such that the given traffic demand can be accommodated even when a single edge or node in the network fails. We derive valid and nonredundant inequalities for the polyhedron of capacity design variables, by exploiting its relationship to connectivity network design and knapsack-like subproblems. A cutting plane algorithm and heuristics for the problem are described, and preliminary computational results are reported. Received August 26, 1993 / Revised version received February 1994     

A note on using alternative second-order models for the subproblems arising in barrier function methods for minimization

Summary. Inequality constrained minimization problems are often solved by considering a sequence of parameterized barrier functions. Each barrier function is approximately minimized and the relevant parameters subsequently adjusted. It is common for the estimated solution to one barrier function problem to be used as a starting estimate for the next. However, this has unfortunate repercussions for the standard Newton-like methods applied to the barrier subproblem. In this note, we consider a class of alternative Newton methods which attempt to avoid such difficulties. Such schemes have already proved of use in the Harwell Subroutine Library quadratic programming codes {\tt VE14} and {\tt VE19}. Received May 2, 1993/Revised form received February 12, 1994     

Absorbing boundary conditions for diffusion equations

Summary. We construct and analyse a family of absorbing boundary conditions for diffusion equations with variable coefficients, curved artifical boundary, and arbitrary convection. It relies on the geometric identification of the Dirichlet to Neumann map and rational interpolation of in the complex plane. The boundary conditions are stable, accurate, and practical for computations. Received December 12, 1992 / Revised version received July 4, 1994     

Orthosymplectic integration of linear Hamiltonian systems

Summary. The authors describe a continuous, orthogonal and symplectic factorization procedure for integrating unstable linear Hamiltonian systems. The method relies on the development of an orthogonal, symplectic change of variables to block triangular Hamiltonian form. Integration is thus carried out within the class of linear Hamiltonian systems. Use of an appropriate timestepping strategy ensures that the symplectic pairing of eigenvalues is automatically preserved. For long-term integrations, as are needed in the calculation of Lyapunov exponents, the favorable qualitative properties of such a symplectic framework can be expected to yield improved estimates. The method is illustrated and compared with other techniques in numerical experiments on the Hénon-Heiles and spatially discretized Sine-Gordon equations. Received December 11, 1995 / Revised version received April 18, 1996     

Comments on Global convergence of the method of shortest residuals by Y. Dai and Y. Yuan

Summary. We show that the example given in [Dai, Y., Yuan, Y. (1999): Global convergence of the method of shortest residuals, Numerische Mathematik 83, 581–598] does not contradict the results of [Pytlak, R. (1994): On the convergence of conjugate gradient algorithms, IMA J. Numerical Analysis 14, 443–460]. Received September 9, 2000 / Revised version received November 28, 2000 / Published online July 25, 2001     

On the convergence of Runge–Kutta methods for stiff non linear differential equations

Summary. This paper studies the convergence properties of general Runge–Kutta methods when applied to the numerical solution of a special class of stiff non linear initial value problems. It is proved that under weaker assumptions on the coefficients of a Runge–Kutta method than in the standard theory of B-convergence, it is possible to ensure the convergence of the method for stiff non linear systems belonging to the above mentioned class. Thus, it is shown that some methods which are not algebraically stable, like the Lobatto IIIA or A-stable SIRK methods, are convergent for the class of stiff problems under consideration. Finally, some results on the existence and uniqueness of the Runge–Kutta solution are also presented. Received November 18, 1996 / Revised version received October 6, 1997     

Extrapolation techniques for ill-conditioned linear systems

Summary. In this paper, the regularized solutions of an ill–conditioned system of linear equations are computed for several values of the regularization parameter . Then, these solutions are extrapolated at by various vector rational extrapolations techniques built for that purpose. These techniques are justified by an analysis of the regularized solutions based on the singular value decomposition and the generalized singular value decomposition. Numerical results illustrate the effectiveness of the procedures. Received June 23, 1997 / Revised version received October 24, 1997     

Rigorous computational shadowing of orbits of ordinary differential equations

Summary. The existence of a true orbit near a numerically computed approximate orbit -- shadowing -- of autonomous system of ordinary differential equations is investigated. A general shadowing theorem for finite time, which guarantees the existence of shadowing in ordinary differential equations and provides error bounds for the distance between the true and the approximate orbit in terms of computable quantities, is proved. The practical use and the effectiveness of this theorem is demonstrated in the numerical computations of chaotic orbits of the Lorenz equations. Received December 15, 1993     

On the convergence of the Newton/log-barrier method

In the Newton/log-barrier method, Newton steps are taken for the log-barrier function for a fixed value of the barrier parameter until a certain convergence criterion is satisfied. The barrier parameter is then decreased and the Newton process is repeated. A naive analysis indicates that Newton’s method does not exhibit superlinear convergence to the minimizer of each instance of the log-barrier function until it reaches a very small neighborhood, namely within O(μ²) of the minimizer, where μ is the barrier parameter. By analyzing the structure of the barrier Hessian and gradient in terms of the subspace of active constraint gradients and the associated null space, we show that this neighborhood is in fact much larger –O(μ^σ) for any σ∈(1,2] – thus explaining why reasonably fast local convergence can be attained in practice. Moreover, we show that the overall convergence rate of the Newton/log-barrier algorithm is superlinear in the number of function/derivative evaluations, provided that the nonlinear program is formulated with a linear objective and that the schedule for decreasing the barrier parameter is related in a certain way to the step length and convergence criteria for each Newton process. Received: October 10, 1997 / Accepted: September 10, 2000?Published online February 22, 2001     

An inexactQP-based method for nonlinear complementarity problems

Summary. We consider a quadratic programming-based method for nonlinear complementarity problems which allows inexact solutions of the quadratic subproblems. The main features of this method are that all iterates stay in the feasible set and that the method has some strong global and local convergence properties. Numerical results for all complementarity problems from the MCPLIB test problem collection are also reported. Received February 24, 1997 / Revised version received September 5, 1997     

On hybrid iterative methods for nonsymmetric systems of linear equations

Summary. Hybrid methods for the solution of systems of linear equations consist of a first phase where some information about the associated coefficient matrix is acquired, and a second phase in which a polynomial iteration designed with respect to this information is used. Most of the hybrid algorithms proposed recently for the solution of nonsymmetric systems rely on the direct use of eigenvalue estimates constructed by the Arnoldi process in Phase I. We will show the limitations of this approach and propose an alternative, also based on the Arnoldi process, which approximates the field of values of the coefficient matrix and of its inverse in the Krylov subspace. We also report on numerical experiments comparing the resulting new method with other hybrid algorithms. Received May 27, 1993 / Revised version received November 14, 1994     

Fast verification of solutions of matrix equations

Summary. In this paper, we are concerned with a matrix equation where A is an real matrix and x and b are n-vectors. Assume that an approximate solution is given together with an approximate LU decomposition. We will present fast algorithms for proving nonsingularity of A and for calculating rigorous error bounds for . The emphasis is on rigour of the bounds. The purpose of this paper is to propose different algorithms, the fastest with flops computational cost for the verification step, the same as for the LU decomposition. The presented algorithms exclusively use library routines for LU decomposition and for all other matrix and vector operations. Received June 16, 1999 / Revised version received January 25, 2001 / Published online June 20, 2001