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Abstract: Traditional mean–variance financial portfolio optimization is based on two sets of parameters, estimates for the asset returns and the variance–covariance matrix. The allocations resulting from both traditional methods and heuristics are very dependent on these values. Given the unreliability of these forecasts, the expected risk and return for the portfolios in the efficient frontier often differ from the expected ones. In this work we present a resampling method based on time-stamping to control the problem. The approach, which is compatible with different evolutionary multiobjective algorithms, is tested with four different alternatives. We also introduce new metrics to assess the reliability of forecast efficient frontiers. [Copyright &y& Elsevier]

Abstract: Constructing a fingerprint database is important to evaluate the performance of an automatic fingerprint recognition system. Because of the difficulty of collecting samples, there are only few benchmark databases available. Moreover, it is hard to evaluate how robust the system is against various environments with those databases. This paper presents a novel method that generates fingerprint images automatically from only a few training samples by using the evolutionary algorithm. Fingerprints generated by the proposed method include similar characteristics of those collected from the corresponding real environment. The proposed method has been verified by comparing with real fingerprints, indicating the usefulness of the method. [Copyright &y& Elsevier]