Comparer des méthodes

	Méthode Floue BWM	Programmation non linéaire
Domaine	Prise de décision	Optimisation
Famille	MCDM	Process / pipeline
Année d'origine	2015 crisp; 2017 variant applicator	2006
Auteur d'origine	Guo, S., Zhao, H.	Jorge Nocedal & Stephen Wright
Type	Triangular-fuzzy Best-to-Others and Others-to-Worst pairwise comparison with nonlinearly-constrained programming	Continuous mathematical optimization
Source fondatrice	Guo, S., Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems	Nocedal, J., & Wright, S. J. (2006). Numerical Optimization (2nd ed.). Springer. ISBN: 978-0-387-30303-1
Alias	—	NLP optimization, Constrained nonlinear optimization, Smooth optimization, Doğrusal olmayan programlama
Apparentées	8	3
Résumé	FUZZY-BWM (Fuzzy BWM — Triangular Fuzzy Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Guo, S., Zhao, H. in 2015 crisp; 2017 variant applicator. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	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.