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Nonlinear Programming/Evidence
Method evidence record

Nonlinear Programming

Nonlinear programming (NLP) is a branch of mathematical optimization concerned with problems in which the objective function or at least one constraint is nonlinear. Formalized comprehensively by Jorge Nocedal and Stephen Wright in their seminal 2006 text, NLP encompasses gradient-based algorithms — including sequential quadratic programming (SQP), interior-point methods, and quasi-Newton approaches — for finding locally or globally optimal solutions to continuous decision problems arising across engineering, economics, and the physical sciences.

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Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Nonlinear Programming
Taxonomic method record · process-pipeline / optimization
  • Nocedal, J., & Wright, S. J. (2006). Numerical Optimization (2nd ed.). Springer. · ISBN 978-0-387-30303-1
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketConvex Optimizationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDynamic Programmingmachine-suggested · Relational suggestion, not evidence.Same method familyStochastic Optimizationmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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