Sciweavers

Share
GECCO
2007
Springer

A gestalt genetic algorithm: less details for better search

9 years 5 months ago
A gestalt genetic algorithm: less details for better search
The basic idea to defend in this paper is that an adequate perception of the search space, sacrificing most of the precision, can paradoxically accelerate the discovery of the most promising solution zones. While any search space can be observed at any scale according to the level of details, there is nothing inherent to the classical metaheuristics to naturally account for this multi-scaling. Nevertheless, the wider the search space the longer the time needed by any metaheuristic to discover and exploit the “promising” zones. Any possibilompress this time is welcome. Abstracting the search space during the search is one such possibility. For instance, a common Ordering Genetic Algorithm (o-GA) is not well suited to efficiently resolve very large instances of the Traveling Salesman Problem (TSP). The mechanism presented miniscent of Gestalt psychology) aims at abstracting the search space by substituting the variables of the problems with macro-versions of them. This substitution...
Christophe Philemotte, Hugues Bersini
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Christophe Philemotte, Hugues Bersini
Comments (0)
books