TY  - GEN
T1  - A memetic algorithm with self-adaptive local search  : TSP as a case study
A1  - Krasnogor, Natalio
A2  - Smith, Jim
LA  - English
UL  - https://catalogo.bibliotecas.unlp.edu.ar/Record/dif.55893
AB  - 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.
NO  - Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
KW  - ALGORITMOS
ER  -