An updated Rosen partitioning algorithm for nonlinear programming

doi:https://doi.org/10.1184/r1/6468344

An updated Rosen partitioning algorithm for nonlinear programming

Richard H. Edahl,Center., Carnegie Mellon University.Engineering Design Research-2018-06-29-Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)

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TL;DRAbstract

Abstract: "Rosen's Partitioning Algorithm for nonlinear programming was developed using a gradient projection method for the master problem. Since then, developments in NLP algorithms have shown the power of the Han-Powell successive quadratic programming algorithm. Here, the formulas necessary for using the Han-Powell algorithm for the master problem of Rosen's algorithm are derived. Sensitivity results are used to handle the 'crossover' problem."

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Abstract: "Rosen's Partitioning Algorithm for nonlinear programming was developed using a gradient projection method for the master problem. Since then, developments in NLP algorithms have shown the power of the Han-Powell successive quadratic programming algorithm. Here, the formulas necessary for using the Han-Powell algorithm for the master problem of Rosen's algorithm are derived. Sensitivity results are used to handle the 'crossover' problem."

Keywords

AlgorithmCrossoverNonlinear programmingSequential quadratic programmingComputer scienceQuadratic programmingMathematical optimizationNonlinear system

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