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| 100 | 1 | _aKrasnogor, Natalio | |
| 245 | 1 | 0 |
_aA memetic algorithm with self-adaptive local search : _bTSP as a case study |
| 300 | _a1 archivo (268,7 kB) | ||
| 500 | _aFormato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca) | ||
| 520 | _aIn this paper we introduce a promising hybridization scheme for a Memetic Algorithm (MA). Our MA is composed of two optimization processes, a Genetic Algorithm and a Monte Carlo method (MC). In contrast with other GA-Monte Carlo hybridized memetic algorithms, in our work the MC stage serves two purposes: -- when the population is diverse it acts like a local search procedure and -- when the population converges its goal is to diversify the search. To achieve this, the MC is self-adaptive based on observations from the underlying GA behavior; the GA controls the long-term optimization process. We present preliminary, yet statistically significant, results on the application of this approach to the TSP problem.We also comment it successful application to a molecular conformational problem: Protein Folding. | ||
| 534 | _aInternational Genetic and Evolutionary Computation Conference (2000 jul., 8-12 : Las Vegas), pp. 897-994. | ||
| 650 | 4 | _aALGORITMOS | |
| 700 | 1 | _aSmith, Jim | |
| 856 | 4 | 0 | _uhttp://goo.gl/HYAhO8 |
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