Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
This paper describes the evolution of new wavelet and scaling numbers for optimized transforms that consistently outperform the 9/7 discrete wavelet transform (DWT) for fingerprin...
Simulated annealing and the (1+1) EA, a simple evolutionary algorithm, are both general randomized search heuristics that optimize any objective function with probability
1 We have developed an approach to acquire complicated user optimization criteria and use them to guide iterative solution improvement. The eectiveness of the approach was tested ...