Título: Greedy seeding procedure for GAs solving a strip packing problem
Autores: Salto, Carolina
Alba Torres, Enrique
Molina, J.M.
Leguizamón, Guillermo
Fecha: 2012-11-02
2007-10
2007
Publicador: Unversidad Nacional de La Plata
Fuente:

Tipo: Objeto de conferencia
Objeto de conferencia
Tema: genetic algorithms
strip packing
seeding
Biology and genetics
Algorithms
Ciencias Informáticas
Informática
Descripción: In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.
Idioma: Inglés