GENE REORDERING AND CONCURRENCY IN GENETIC ALGORITHMS 

	              Şehitoğlu, Onur Tolga 

	     Ph.D., Department of Computer Engineering 
	     Supervisor: Assoc. Prof.  Dr. Göktürk Uçoluk 
	               August 2002, 90 pages 

This study first introduces an order-free chromosome encoding to
enhance the performance of genetic algorithms by learning the linkage
of building blocks in non-binary encodings. The method introduces a
measure called `affinity' which is based  on the statistical properties
of gene valuations in the population. It uses the affinity values of the
local and global gene pairs to construct a global permutation with tight
building block positioning. Method is tested and experimental results
are shown for a group of deceptive and real life test problems.

Then, study proposes a gene level concurrency model  where each gene
position is implemented on a different process. This combines the
advantages of implicit parallelism and a chromosome structure free
approach.  It also helps implementation of gene reordering method
introduced and probably other non-linear chromosome encodings.

Keywords: 
genetic algorithms, concurrency, reordering, linkage learning,
deceptive problem