|
|
|
|
| LEADER |
00000naa a2200000 a 4500 |
| 003 |
AR-LpUFIB |
| 005 |
20250311170422.0 |
| 008 |
230201s2000 xx o 000 0 eng d |
| 024 |
8 |
|
|a DIF-M6700
|b 6837
|z DIF006111
|
| 040 |
|
|
|a AR-LpUFIB
|b spa
|c AR-LpUFIB
|
| 100 |
1 |
|
|a Krasnogor, Natalio
|
| 245 |
1 |
0 |
|a A memetic algorithm with self-adaptive local search :
|b TSP as a case study
|
| 300 |
|
|
|a 1 archivo (268,7 kB)
|
| 500 |
|
|
|a Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
|
| 520 |
|
|
|a In 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 |
|
|
|a International Genetic and Evolutionary Computation Conference (2000 jul., 8-12 : Las Vegas), pp. 897-994.
|
| 650 |
|
4 |
|a ALGORITMOS
|
| 700 |
1 |
|
|a Smith, Jim
|
| 856 |
4 |
0 |
|u http://goo.gl/HYAhO8
|
| 942 |
|
|
|c CP
|
| 952 |
|
|
|0 0
|1 0
|4 0
|6 A0446
|7 3
|8 BD
|9 81071
|a DIF
|b DIF
|d 2025-03-11
|l 0
|o A0446
|r 2025-03-11 17:04:22
|u http://catalogo.info.unlp.edu.ar/meran/getDocument.pl?id=726
|w 2025-03-11
|y CP
|
| 999 |
|
|
|c 55893
|d 55893
|
