Transition Models as an incremental approach for problem solving in Evolutionary Algorithms (bibtex)
by A Defaweux, T Lenaerts, van Hemert, J and J Parent
Abstract:
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model. It lets building units of a solution interact and then uses an evolutionary process to merge these units toward a full solution for the problem at hand. The paper provides a preliminary study on the evolutionary dynamics of this model as well as an empirical comparison with other evolutionary techniques on binary constraint satisfaction.
Reference:
Transition Models as an incremental approach for problem solving in Evolutionary Algorithms (A Defaweux, T Lenaerts, van Hemert, J and J Parent), In Genetic and Evolutionary Computation (H-G Beyer et al., ed.), ACM Press, volume 7, 2005.
Bibtex Entry:
@article{DLHP2005,
	_day = {25},
	abstract = {This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model. It lets building units of a solution interact and then uses an evolutionary process to merge these units toward a full solution for the problem at hand. The paper provides a preliminary study on the evolutionary dynamics of this model as well as an empirical comparison with other evolutionary techniques on binary constraint satisfaction.},
	author = {A Defaweux and T Lenaerts and van Hemert, J and J Parent},
	date-added = {2008-08-18 12:44:11 +0100},
	date-modified = {2008-08-18 12:44:11 +0100},
	editor = {H-G Beyer et al.},
	journal = {Genetic and Evolutionary Computation},
	keywords = {constraint satisfaction; evolutionary computation},
	pages = {599--606},
	pdf = {http://www.vanhemert.co.uk/publications/gecco2005-Transition_Models_as_an_incremental_approach_for_problem_solving_in_Evolutionary_Algorithms.pdf},
	publisher = {{ACM} Press},
	title = {Transition Models as an incremental approach for problem solving in Evolutionary Algorithms},
	volume = {7},
	year = {2005}}
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