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Nonlinear Constrained Optimization: Methods and Software

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ARGONNE NATIONAL LABORATORY9700 South Cass AvenueArgonne, Illinois 60439Nonlinear Constrained optimization : Methods and SoftwareSven Leyffer and Ashutosh MahajanMathematics and Computer Science DivisionPreprint ANL/MCS-P1729-0310March 17, 2010This work was supported by the Office of Advanced Scientific Computing Research, Office of Science, Departmentof Energy, under Contract Background and Introduction12 Convergence Test and Termination Conditions23 Local Model: Improving a Solution Linear and Quadratic Programming . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54 Globalization Strategy: Convergence from Remote Starting Lagrangian Methods .

Algorithms for NCOs are categorized by the choice they implement for each of these funda-mental components. In the next section, we review the fundamental building blocks of methods for nonlinearly constrained optimization. Notation: Throughout this paper, we denote iterates by x k;k= 1;2;:::, and we use subscripts to

  Methods, Software, Algorithm, Nonlinear, Optimization, Constrained, Nonlinear constrained optimization, Methods and software

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