Simulated annealing and improved genetic algorithms for path testing. (c1997)

Joumaa, Rania

dc.contributor.author	Joumaa, Rania
dc.date.accessioned	2011-04-08T12:39:11Z
dc.date.available	2011-04-08T12:39:11Z
dc.date.copyright	1997	en_US
dc.date.issued	2011-04-08
dc.date.submitted	1997-06
dc.identifier.uri	http://hdl.handle.net/10725/335
dc.description	Includes bibliographical references (l. 45-46).	en_US
dc.description.abstract	In this work, we formulate the path testing problem as an optimization problem by combining two previous ideas, and we propose a simulated annealing (SA) algorithm to solve it. We also improve a genetic algorithm (GA) that has been previously used. Our experimental results show that the SA and improved GA are useful for path testing and that they have comparable behavior and performance.	en_US
dc.language.iso	en	en_US
dc.subject	Computer software -- Testing	en_US
dc.subject	Simulated annealing (Mathematics)	en_US
dc.subject	Genetic algorithms	en_US
dc.title	Simulated annealing and improved genetic algorithms for path testing. (c1997)	en_US
dc.type	Thesis	en_US
dc.term.submitted	Spring	en_US
dc.author.degree	MS in Computer Science	en_US
dc.author.school	Arts and Sciences	en_US
dc.author.commembers	Dr. George Nassar
dc.author.commembers	Dr. Haidar Harmanany
dc.author.woa	RA	en_US
dc.description.physdesc	1 bound copy: v, 46 leaves; ill.; 30 cm. available at RNL.	en_US
dc.author.division	Computer Science	en_US
dc.author.advisor	Dr. Nashat Mansour
dc.identifier.doi	https://doi.org/10.26756/th.1997.15	en_US
dc.publisher.institution	Lebanese American University	en_US