Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Algoritmo Push-Relabel× | Algoritmo de Bellman-Ford× | |
|---|---|---|
| Campo | Investigación operativa | Investigación operativa |
| Familia | Machine learning | Machine learning |
| Año de origen≠ | 1988 | 1956 |
| Autor original≠ | Andrew V. Goldberg and Robert E. Tarjan | Richard Bellman and Lester R. Ford |
| Tipo | algorithm | algorithm |
| Fuente seminal≠ | Goldberg, A. V., & Tarjan, R. E. (1988). A new approach to the maximum flow problem. Journal of the ACM, 35(4), 921-940. DOI ↗ | Bellman, R. (1958). On a routing problem. Quarterly of Applied Mathematics, 16(1), 87-90. DOI ↗ |
| Alias | preflow-push algorithm, Goldberg-Tarjan algorithm | Bellman-Ford method, Bellman algorithm |
| Relacionados | 3 | 3 |
| Resumen≠ | The Push-Relabel Algorithm, developed by Andrew V. Goldberg and Robert E. Tarjan in 1988, is a highly efficient method for computing maximum flow in networks. Unlike augmenting path methods, it maintains a preflow and uses local push and global relabeling operations to drive flow toward the sink, achieving superior worst-case complexity. | The Bellman-Ford Algorithm, developed by Richard Bellman and Lester R. Ford in the 1950s, is a fundamental algorithm for computing shortest paths in weighted graphs that may contain negative edge weights. Unlike Dijkstra's algorithm, it correctly handles negative weights and can detect the presence of negative-weight cycles. |
| ScholarGateConjunto de datos ↗ |
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