Methoden vergleichen

	Multikriterielle Mikrosimulation	Mehrzieloptimierung – Gleichzeitige Optimierung widerstreitender Ziele
Fachgebiet	Simulation	Simulation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1957 (microsimulation); 2000s (multi-objective extension)	1896 (concept); 1989–2002 (evolutionary algorithms era)
Urheber	Orcutt, G. H. (microsimulation); multi-objective extension developed by policy modeling community	Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
Typ	Simulation-based policy evaluation	Optimization framework
Wegweisende Quelle	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116-123.	Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
Aliasnamen	MO-Microsim, Multi-criteria microsimulation, Multi-objective policy microsimulation, MOMS	MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization
Verwandt	5	3
Zusammenfassung	Multi-objective microsimulation extends the classic microsimulation framework by simultaneously tracking and optimizing several competing policy objectives — such as efficiency, equity, fiscal cost, and social welfare — across a heterogeneous population of individual units. It produces a Pareto frontier of policy options rather than a single recommended solution, enabling transparent tradeoff analysis for complex policy decisions.	Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis.