विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-उद्देश्यीय रैखिक प्रोग्रामिंग (MOLP)× | लक्ष्य प्रोग्रामिंग× | रैखिक प्रोग्रामन× | |
|---|---|---|---|
| क्षेत्र≠ | अनुकरण | निर्णयन | अनुकूलन |
| परिवार≠ | Process / pipeline | MCDM | Process / pipeline |
| उद्भव वर्ष≠ | 1955–1986 | 1955 | 1947 |
| प्रवर्तक≠ | Steuer, R. E.; Charnes, A.; Cooper, W. W. | Charnes, A., Cooper, W. W. | George B. Dantzig |
| प्रकार≠ | Mathematical optimization / vector optimization | Multi-objective optimisation — weighted/lexicographic goal deviation minimisation | Mathematical programming / continuous optimization |
| मौलिक स्रोत≠ | Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468 | Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science DOI ↗ | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| उपनाम≠ | MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization | — | LP, linear optimization, Doğrusal Programlama (LP) |
| संबंधित≠ | 3 | 8 | 4 |
| सारांश≠ | Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals. | 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. | Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences. |
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