DocumentCode :
2995934
Title :
Multiple single objective Pareto sampling
Author :
Hughes, Evan J.
Author_Institution :
Dept. of Aerosp., Power & Sensors, Cranfield Univ., England, UK
Volume :
4
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
2678
Abstract :
We detail a new nonPareto evolutionary multiobjective algorithm, multiple single objective Pareto sampling (MSOPS), that performs a parallel search of multiple conventional target vector based optimisations, e.g. weighted min-max. The method can be used to generate the Pareto set and analyse problems with large numbers of objectives. The method allows bounds and discontinuities of the Pareto set to be identified and the shape of the surface to be analysed, despite not being able to visualise the surface easily. A new combination metric is also introduced that allows the shape of the objective surface that gives rise to discontinuities in the Pareto surface to be analysed easily.
Keywords :
Pareto optimisation; evolutionary computation; sampling methods; search problems; Pareto set; Pareto surface; combination metric; evolutionary multiobjective algorithm; multiple single objective Pareto sampling; parallel search; target vector based optimizations; Algorithm design and analysis; Educational institutions; Evolutionary computation; Pareto analysis; Pareto optimization; Sampling methods; Shape; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299427
Filename :
1299427
Link To Document :
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