Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Programación por Metas Estocástica× | Programación por Metas Multiobjetivo× | |
|---|---|---|
| Campo | Simulación | Simulación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1968 | 1961 |
| Autor original≠ | Contini, B. (building on Charnes & Cooper's chance-constrained programming) | Charnes, A. and Cooper, W. W. |
| Tipo≠ | Stochastic multi-goal optimization | Mathematical programming / multi-criteria optimization |
| Fuente seminal≠ | Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗ | Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 978-0471148258 |
| Alias | SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming | MOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming |
| Relacionados≠ | 6 | 4 |
| Resumen≠ | Stochastic 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. | Multi-Objective Goal Programming (MOGP) is a mathematical programming technique that simultaneously pursues several aspirational targets by minimizing weighted deviations from each goal. Rooted in Charnes and Cooper's original goal programming framework (1961), MOGP extends it to handle multiple competing objectives, making it indispensable in operations research, supply chain design, resource allocation, and policy analysis where decision-makers must satisfy — or come close to — multiple conflicting requirements at once. |
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