विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| जेनेटिक एल्गोरिथम× | मिश्रित-पूर्णांक प्रोग्रामिंग× | |
|---|---|---|
| क्षेत्र≠ | अनुकूलन | अनुकरण |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 1975 | 1958–1960 |
| प्रवर्तक≠ | John Henry Holland | Ralph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960) |
| प्रकार≠ | Population-based metaheuristic | Mathematical optimization |
| मौलिक स्रोत≠ | Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗ | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432 |
| उपनाम≠ | GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon | MIP, Mixed-Integer Linear Programming, MILP, Integer Programming |
| संबंधित≠ | 5 | 6 |
| सारांश≠ | 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. | 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. |
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