পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| পূর্ণসংখ্যা প্রোগ্রামিং× | দৃঢ় অপ্টিমাইজেশন× | |
|---|---|---|
| ক্ষেত্র | অনুকূলকরণ | অনুকূলকরণ |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1958 | 1970s theoretical roots; modern tractable form from late 1990s–2004 |
| প্রবর্তক≠ | 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) |
| ধরন≠ | Mathematical optimisation — exact combinatorial method | Mathematical programming framework |
| মৌলিক উৎস≠ | 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 |
| অপর নাম≠ | IP, MIP, mixed-integer programming, mixed-integer linear programming | minimax optimization, worst-case optimization, Gürbüz Optimizasyon (Robust Optimization) |
| সম্পর্কিত≠ | 4 | 5 |
| সারসংক্ষেপ≠ | 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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