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Multi-Objective Mixed-Integer Programming×Mehrkriterielle Lineare Programmierung (MOLP)×
FachgebietSimulationSimulation
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr1980s–2000s1955–1986
UrheberEhrgott, M.; Mavrotas, G. and others in multi-criteria optimizationSteuer, R. E.; Charnes, A.; Cooper, W. W.
TypMathematical optimizationMathematical optimization / vector optimization
Wegweisende QuelleEhrgott, M. (2005). Multicriteria Optimization (2nd ed.). Springer, Berlin. ISBN: 9783540213987Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468
AliasnamenMO-MIP, Multi-criteria MIP, MOMIP, Multi-objective MILPMOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization
Verwandt53
ZusammenfassungMulti-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.Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals.
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ScholarGateMethoden vergleichen: Multi-objective mixed-integer programming · Multi-objective linear programming. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare