In a standard NP-complete optimization problem we introduce an interpolating algorithm between the quick decrease along the gradient (greedy dynamics) and a slow decrease close to the level curves (reluctant dynamics). We find that for a fixed elapsed computer time the best performance of the optimization is reached at a special value of the interpolation parameter, considerably improving the results of the pure cases greedy and reluctant.
@article{arxiv.math-ph/0309063,
title = {Interpolating Greedy and Reluctant Algorithms},
author = {P. Contucci and C. Giardina' and C. Giberti and F. Unguendoli and C. Vernia},
journal= {arXiv preprint arXiv:math-ph/0309063},
year = {2007}
}