Some implementation issues associated with multidimensional interval Newton methods |
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Authors: | John J Dinkel Marietta Tretter Danny Wong |
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Affiliation: | 1. Associate Provost for Computing and Information Systems, Texas A&M University, 119 Teague Building, 77843, College Station, TX 2. Department of Business Analysis College of Business Administration, Texas A&M University, 77843, College Station, TX 3. Faulty of Business Administration, The Chinese University of Hong Kong, Shatin N. T., Hong Kong
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Abstract: | This paper presents the development of an optimal interval Newton method for systems of nonlinear equations. The context of solving such systems of equations is that of optimization of nonlinear mathematical programs. The modifications of the interval Newton method presented in this paper provide computationally effective enhancements to the general interval Newton method. The paper demonstrates the need to compute an optimal step length in the interval Newton method in order to guarantee the generation of a sequence of improving solutions. This method is referred to as the optimal Newton method and is implemented in multiple dimensions. Secondly, the paper demonstrates the use of the optimal interval Newton method as a feasible direction method to deal with non-negativity constraints. Also, included in this implementation is the use of a matrix decomposition technique to reduce the computational effort required to compute the Hessian inverse in the interval Newton method. The methods are demonstrated on several problems. Included in these problems are mathematical programs with perturbations in the problem coefficients. The numerical results clearly demonstrate the effectiveness and efficiency of these approaches. |
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