Sammenlign metoder

	Deterministisk heltallsprogrammering – Eksakt optimering med faste parametere	Multi-Objective Mixed-Integer Programming
Fagfelt	Simulering	Simulering
Familie	Process / pipeline	Process / pipeline
Opprinnelsesår	1958–1960	1980s–2000s
Opphavsperson	Gomory, R. E.; Dantzig, G. B.; Land, A. H.; Doig, A. G.	Ehrgott, M.; Mavrotas, G. and others in multi-criteria optimization
Type	Mathematical programming / combinatorial optimization	Mathematical optimization
Opprinnelig kilde	Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. John Wiley & Sons, New York. ISBN: 9780471359432	Ehrgott, M. (2005). Multicriteria Optimization (2nd ed.). Springer, Berlin. ISBN: 9783540213987
Alias	Deterministic MIP, Deterministic MILP/MIQP, Classical Mixed-Integer Programming, Deterministic MIP Optimization	MO-MIP, Multi-criteria MIP, MOMIP, Multi-objective MILP
Relaterte	6	5
Sammendrag	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.	Multi-Objective Mixed-Integer Programming (MO-MIP) is an optimization framework that simultaneously optimizes two or more conflicting objective functions subject to linear or nonlinear constraints, where some decision variables are restricted to integer values and others are continuous. It is widely applied in engineering design, supply chain planning, resource allocation, and scheduling problems that require discrete choices alongside continuous quantities.