Smoothing methods for convex inequalities and linear complementarity problems
نویسندگان
چکیده
منابع مشابه
Smoothing methods for convex inequalities and linear complementarity problems
A smooth approximation p(x;) to the plus function: maxfx; 0g, is obtained by integrating the sigmoid function 1=(1 + e ?x), commonly used in neural networks. By means of this approximation, linear and convex inequalities are converted into smooth, convex unconstrained minimization problems, the solution of which approximates the solution of the original problem to a high degree of accuracy for ...
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We present a new algorithm for the solution of general (not necessarily monotone) complementarity problems. The algorithm is based on a reformulation of the complementarity problem as a nonsmooth system of equations by using the Fischer-Burmeister function. We use an idea by Chen, Qi and Sun and apply a Jacobian smoothing method (which is a mixture between nonsmooth Newton and smoothing methods...
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In this paper, we present a new smoothing approach to solve general nonlinear complementarity problems. Under the P0 condition on the original problems, we prove some existence and convergence results . We also present an error estimate under a new and general monotonicity condition. The numerical tests confirm the efficiency of our proposed methods.
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The mixed complementarity problem can be reformulated as a nonsmooth equation by using the median operator. In this paper, we rst study some useful properties of this reformulation and then derive the Chen-Harker-Kanzow-Smale smoothing function for the mixed complementarity problem. On the basis of this smoothing function, we present a smoothing Newton method for solving the mixed complementari...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 1995
ISSN: 0025-5610,1436-4646
DOI: 10.1007/bf01592244