SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization

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SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization (2002)

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by Philip E. Gill , Walter Murray , Michael A. Saunders

Citations:

596 - 24 self

BibTeX

@MISC{Gill02snopt:an,
    author = {Philip E. Gill and Walter Murray and Michael A. Saunders},
    title = {SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization},
    year = {2002}
}

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Abstract

Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first derivatives are available, and that the constraint gradients are sparse. We discuss

Keyphrases

large-scale constrained optimization sqp algorithm constraint gradient general inequality constraint smooth nonlinear function sequential quadratic programming first derivative constrained optimization problem

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