विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-उद्देश्यीय रैखिक प्रोग्रामिंग (MOLP)× | बहु-उद्देश्यीय अनुकूलन× | |
|---|---|---|
| क्षेत्र | अनुकरण | अनुकरण |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1955–1986 | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| प्रवर्तक≠ | Steuer, R. E.; Charnes, A.; Cooper, W. W. | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| प्रकार≠ | Mathematical optimization / vector optimization | Optimization framework |
| मौलिक स्रोत≠ | Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468 | Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396 |
| उपनाम | MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| संबंधित | 3 | 3 |
| 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. | Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis. |
| ScholarGateडेटासेट ↗ |
|
|