ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Стохастическое целевое программирование×Программирование целевых установок×
ОбластьИмитационное моделированиеПринятие решений
СемействоProcess / pipelineMCDM
Год появления19681955
Автор методаContini, B. (building on Charnes & Cooper's chance-constrained programming)Charnes, A., Cooper, W. W.
ТипStochastic multi-goal optimizationMulti-objective optimisation — weighted/lexicographic goal deviation minimisation
Основополагающий источникContini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗
Другие названияSGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming
Связанные68
СводкаStochastic Goal Programming (SGP) extends classical goal programming to handle uncertainty in goal targets, constraint coefficients, or right-hand-side parameters. By incorporating probabilistic constraints and stochastic objective components, it finds solutions that satisfy multiple goals at acceptable probability levels, making it suitable for decision problems where data are inherently uncertain or variable.GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 1 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Stochastic Goal Programming · GOAL-PROGRAMMING. Получено 2026-06-15 из https://scholargate.app/ru/compare