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Determinističko mješovito-cjelobrojno programiranje×Robusno mješovito cjelobrojno programiranje×
PodručjeSimulacijaSimulacija
ObiteljProcess / pipelineProcess / pipeline
Godina nastanka1958–19601998–2004
TvoracGomory, R. E.; Dantzig, G. B.; Land, A. H.; Doig, A. G.Ben-Tal & Nemirovski; Bertsimas & Sim
VrstaMathematical programming / combinatorial optimizationDeterministic robust reformulation of MIP under uncertainty
Temeljni izvorNemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. John Wiley & Sons, New York. ISBN: 9780471359432Bertsimas, D., Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53. DOI ↗
Drugi naziviDeterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP OptimizationRMIP, Robust MIP, Uncertain MIP, Robust MILP/MIQP
Srodne64
SažetakDeterministic 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.Robust Mixed-Integer Programming (RMIP) combines mixed-integer programming with robust optimization to find solutions that remain feasible and near-optimal despite uncertain parameters. Instead of assuming fixed data, it protects decisions against adversarial or worst-case realizations of uncertain inputs, using an explicit uncertainty set to control the degree of conservatism while preserving the combinatorial structure of integer decisions.
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ScholarGateUsporedite metode: Deterministic Mixed-Integer Programming · Robust Mixed-Integer Programming. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare