Title :
Constraint handling with uncertain and noisy multi-objective evolution
Author_Institution :
Dept. of Aerosp., Power & Sensors, R. Mil. Coll. of Sci., Shrivenham, UK
Abstract :
Many real world problems are constrained and have multiple objectives that must be satisfied. To compound the optimisation challenge, systems are often noisy or uncertain, leading to errors in the objective calculations. This paper develops theory to help reduce the effects of noise and uncertainty on constrained evolutionary optimisation processes. Experimental results are presented for generating Pareto surfaces with two different types of noise and also with constraints and designer preferences
Keywords :
constraint handling; evolutionary computation; uncertain systems; Pareto surface generation; constrained evolutionary optimisation; constraint handling; errors; experimental results; noisy multi-objective evolution; optimisation; uncertain evolution; Biological cells; Constraint theory; Educational institutions; Evolutionary computation; Noise generators; Noise reduction; Noise robustness; Probability; Statistical distributions; Uncertainty;
Conference_Titel :
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location :
Seoul
Print_ISBN :
0-7803-6657-3
DOI :
10.1109/CEC.2001.934294
