Krahasoni metodat

	Optimizimi Stokastik me shumë objektivë	Optimizimi Robust me Shumë Objekte
Fusha	Simulimi	Simulimi
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1990s–2000s	2006
Krijuesi	Various (Fonseca, Fleming, Deb, Zitzler, and others)	Deb, K. & Gupta, H.
Lloji	Stochastic metaheuristic optimization	Optimization framework
Burimi themelues	Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396	Deb, K., & Gupta, H. (2006). Introducing robustness in multi-objective optimization. Evolutionary Computation, 14(4), 463–494.
Emërtime të tjera	SMOO, Stochastic MOO, Multi-objective optimization under uncertainty, Robust multi-objective optimization	RMOO, Robust MOO, Robust Pareto Optimization, Uncertainty-Robust Multi-Objective Optimization
Të lidhura	5	4
Përmbledhja	Stochastic Multi-Objective Optimization (SMOO) is a class of methods that simultaneously optimizes two or more conflicting objectives when parameters, costs, or constraints are uncertain or random. Rather than a single optimal solution, it produces a Pareto front of non-dominated solutions, each representing a different balance among objectives under the modeled uncertainty.	Robust Multi-Objective Optimization (RMOO) is a framework for finding solutions that simultaneously optimize multiple conflicting objectives while remaining insensitive to perturbations in decision variables or problem parameters. Unlike classical MOO, RMOO explicitly incorporates uncertainty into the optimization loop, producing a robust Pareto front whose members perform well not only at the nominal design point but also across a neighbourhood of plausible operating conditions.