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Pengaturcaraan Kuadratik (QP)×Pengaturcaraan Linear×
BidangPengoptimumanPengoptimuman
KeluargaProcess / pipelineProcess / pipeline
Tahun asal19561947
PengasasMarguerite Frank & Philip WolfeGeorge B. Dantzig
JenisConstrained mathematical optimizationMathematical programming / continuous optimization
Sumber perintisFrank, M., & Wolfe, P. (1956). An algorithm for quadratic programming. Naval Research Logistics Quarterly, 3(1–2), 95–110. DOI ↗Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136
AliasQP Optimization, Quadratic Optimization, Convex Quadratic Programming, İkinci Dereceden ProgramlamaLP, linear optimization, Doğrusal Programlama (LP)
Berkaitan24
RingkasanQuadratic Programming (QP) is a class of constrained mathematical optimization in which the objective function is quadratic and the constraints are linear. Formalized by Frank and Wolfe (1956) through their gradient-based feasible-direction algorithm, QP is foundational in operations research, finance, machine learning, and engineering design wherever one must minimize a convex (or non-convex) quadratic cost subject to linear feasibility conditions.Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences.
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ScholarGateBandingkan kaedah: Quadratic Programming · Linear Programming. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare