@incollection{EH99,
	_day = {01},
	abstract = {In this chapter we describe a problem independent method for treating constrain ts in an evolutionary algorithm. Technically, this method amounts to changing the defini tion of the fitness function during a run of an EA, based on feedback from the search pr ocess. Obviously, redefining the fitness function means redefining the problem to be sol ved. On the short term this deceives the algorithm making the fitness values deteriorate , but as experiments clearly indicate, on the long run it is beneficial. We illustrate t he power of the method on different constraint satisfaction problems and point out other application areas of this technique.},
	author = {AE Eiben and van Hemert, J},
	booktitle = {New ideas in optimization},
	chapter = {26},
	date-added = {2008-08-18 12:44:37 +0100},
	date-modified = {2008-08-18 12:44:37 +0100},
	editor = {D Corne and M Dorigo and F Glover},
	keywords = {constraint satisfaction},
	notedisabled = {\textsc{Cited by 27 (Google Scholar 2009/01/19)}},
	pages = {389--402},
	pdf = {http://www.vanhemert.co.uk/publications/chapter.SAW-ing_EAs:_adapting_the_fitness_function_for_solving_constrained_problems.pdf},
	ps.gz = {http://www.vanhemert.co.uk/publications/chapter.SAW-ing_EAs:_adapting_the_fitness_function_for_solving_constrained_problems.ps.gz},
	publisher = {McGraw-Hill, London},
	title = {{SAW}-ing {EA}s: adapting the fitness function for solving constrained problems},
	year = {1999}}