Natural SciencesComputer ScienceMathematicsAlgorithmsOptimizationParallel AlgorithmsEvolutionary ComputationEvolutionary OptimizationMetaheuristic OptimizationMulti-objective OptimizationMultiobjective OptimizationPareto OptimalityMulti-objective Evolutionary AlgorithmsMulti-objective Evolutionary ComputationMultiobjective Evolutionary AlgorithmsParallel SearchParallel Search AlgorithmsPareto AnalysisPareto Optimal SolutionPareto Set Generation
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.
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