Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Programim me numra të plotë× | Optimizimi robust× | |
|---|---|---|
| Fusha | Optimizimi | Optimizimi |
| Familja | Process / pipeline | Process / pipeline |
| Viti i origjinës≠ | 1958 | 1970s theoretical roots; modern tractable form from late 1990s–2004 |
| Krijuesi≠ | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) | Ben-Tal, El Ghaoui & Nemirovski (seminal book, 2009); Bertsimas & Sim (tractable polyhedral formulation, 2004) |
| Lloji≠ | Mathematical optimisation — exact combinatorial method | Mathematical programming framework |
| Burimi themelues≠ | Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669 | Ben-Tal, A., El Ghaoui, L. & Nemirovski, A. (2009). Robust Optimization. Princeton University Press. ISBN: 9780691143682 |
| Emërtime të tjera≠ | IP, MIP, mixed-integer programming, mixed-integer linear programming | minimax optimization, worst-case optimization, Gürbüz Optimizasyon (Robust Optimization) |
| Të lidhura≠ | 4 | 5 |
| Përmbledhja≠ | Integer programming (IP), also called mixed-integer programming (MIP) when only some variables are restricted to whole numbers, is a branch of mathematical optimisation in which some or all decision variables must take integer or binary values. Building on linear programming, it was formalised through Ralph Gomory's cutting-plane method (1958) and the Land-and-Doig branch-and-bound algorithm (1960), and it has since become the standard exact framework for scheduling, assignment, routing, and resource-allocation problems. | Robust optimization is a mathematical programming framework, formalised by Ben-Tal and Nemirovski in the late 1990s and made broadly tractable by Bertsimas and Sim (2004), that finds decisions guaranteed to perform acceptably under every scenario within a predefined uncertainty set — rather than assuming parameter values are known exactly. Instead of optimising for a single expected outcome, it minimises the worst-case objective across all plausible realisations of uncertain data. |
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