विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| स्टोकेस्टिक लीनियर प्रोग्रामिंग× | स्टोकेस्टिक गोल प्रोग्रामिंग× | |
|---|---|---|
| क्षेत्र | अनुकरण | अनुकरण |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1955 | 1968 |
| प्रवर्तक≠ | George B. Dantzig | Contini, B. (building on Charnes & Cooper's chance-constrained programming) |
| प्रकार≠ | Stochastic optimization model | Stochastic multi-goal optimization |
| मौलिक स्रोत≠ | Dantzig, G. B., & Madansky, A. (1961). On the solution of two-stage linear programs under uncertainty. Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, 165–176. link ↗ | Contini, B. (1968). A stochastic approach to goal programming. Operations Research, 16(3), 576–586. DOI ↗ |
| उपनाम | SLP, Stochastic LP, Linear Programming under Uncertainty, Two-Stage SLP | SGP, Stochastic GP, Chance-Constrained Goal Programming, Probabilistic Goal Programming |
| संबंधित≠ | 5 | 6 |
| सारांश≠ | Stochastic Linear Programming (SLP) extends classical linear programming to settings where some model parameters — costs, demands, resource availability — are uncertain and modeled as random variables. By optimizing expected costs over a probability distribution of scenarios, SLP produces decisions that remain feasible and near-optimal across a range of possible futures rather than for a single assumed state of the world. | 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. |
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