Title :
Multiple single objective Pareto sampling
Author_Institution :
Dept. of Aerosp., Power & Sensors, Cranfield Univ., England, UK
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;
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
DOI :
10.1109/CEC.2003.1299427