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.
Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.
Source record
Recorded
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Nonlinear Programming
Taxonomic method recordprocess-pipelineoptimization
Nocedal, J., & Wright, S. J. (2006). Numerical Optimization (2nd ed.). Springer. · ISBN 978-0-387-30303-1
Open full method1 recorded citation, copied from the method source record.
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Related methods
Suggested3
Generated from the method graph and shown as machine-suggested relations. No evidence claim is inferred.
- Taxonomic bucketConvex Optimization
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketDynamic Programming
machine-suggestedRelational suggestion, not evidence.
- Same method familyStochastic Optimization
machine-suggestedRelational suggestion, not evidence.