Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Нелінійний метод найкращого та найгіршого (Non-linear Best Worst Method)× | Метод Найкращого-Найгіршого (BWM)× | Нелінійне програмування× | |
|---|---|---|---|
| Галузь≠ | Прийняття рішень | Прийняття рішень | Оптимізація |
| Родина≠ | MCDM | MCDM | Process / pipeline |
| Рік появи≠ | 2016 | 2015 | 2006 |
| Автор методу≠ | Extended development of Rezaei's BWM framework | Rezaei, J. | Jorge Nocedal & Stephen Wright |
| Тип≠ | Non-linear optimization for flexible weight derivation | Pairwise comparison (best-to-others + others-to-worst vectors), LP | Continuous mathematical optimization |
| Основоположне джерело≠ | Rezaei, J. (2015). Best-worst multi-criteria decision-making method: Some properties and a linear model. Journal of Cleaner Production, 229, 976-985. DOI ↗ | Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega DOI ↗ | Nocedal, J., & Wright, S. J. (2006). Numerical Optimization (2nd ed.). Springer. ISBN: 978-0-387-30303-1 |
| Інші назви≠ | Non-linear BWM, Nonlinear BWM | — | NLP optimization, Constrained nonlinear optimization, Smooth optimization, Doğrusal olmayan programlama |
| Пов'язані≠ | 3 | 8 | 3 |
| Підсумок≠ | Non-linear BWM is a variant of the Best Worst Method that replaces the linear programming formulation with non-linear optimization. Instead of minimizing the maximum deviation (Chebyshev distance), it minimizes the sum of squared deviations (L2 norm). This provides more flexible weight derivation and better accommodates uncertain or fuzzy preferences. | BWM (Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Rezaei, J. in 2015. 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. |
| ScholarGateНабір даних ↗ |
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