विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मिश्रित-पूर्णांक प्रोग्रामिंग× | जेनेटिक एल्गोरिथम× | |
|---|---|---|
| क्षेत्र≠ | अनुकरण | अनुकूलन |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1958–1960 | 1975 |
| प्रवर्तक≠ | Ralph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960) | John Henry Holland |
| प्रकार≠ | Mathematical optimization | Population-based metaheuristic |
| मौलिक स्रोत≠ | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432 | Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗ |
| उपनाम≠ | MIP, Mixed-Integer Linear Programming, MILP, Integer Programming | GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally. | A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail. |
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