方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 确定性混合整数规划× | 确定性动态规划× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1958–1960 | 1957 |
| 提出者≠ | Gomory, R. E.; Dantzig, G. B.; Land, A. H.; Doig, A. G. | Richard E. Bellman |
| 类型≠ | Mathematical programming / combinatorial optimization | Exact sequential optimization algorithm |
| 开创性文献≠ | Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. John Wiley & Sons, New York. ISBN: 9780471359432 | Bellman, R. E. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516 |
| 别名 | Deterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP Optimization | DDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic Programming |
| 相关 | 6 | 6 |
| 摘要≠ | Deterministic Mixed-Integer Programming (MIP) is a mathematical optimization framework that finds the provably optimal solution to problems involving both continuous and integer decision variables under fully known, fixed coefficients and constraints. It is the foundational workhorse of operations research when all data are treated as certain. | Deterministic Dynamic Programming (DDP) is a mathematical optimization technique that decomposes a multi-stage decision problem into a sequence of simpler subproblems, solving them exactly when all system parameters — transition functions, costs, and rewards — are known with certainty. It guarantees a globally optimal policy via Bellman's principle of optimality. |
| ScholarGate数据集 ↗ |
|
|