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dc.contributor.authorAtluri, Kartheek
dc.date.accessioned2014-03-04T18:21:08Z
dc.date.available2014-03-04T18:21:08Z
dc.date.issued2009-12
dc.identifier.otheratluri_kartheek_200912_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/atluri_kartheek_200912_ms
dc.identifier.urihttp://hdl.handle.net/10724/25994
dc.description.abstractThe focus of this project is on three nature inspired search techniques. Inspired by human evolution the Genetic Algorithm (GA) is the most famous and widely used search technique. The second search technique is Particle Swarm Optimization (PSO), which originated with the intent to simulate the graceful but unpredictable choreography of a bird flock. The third and final technique is Simulated Annealing (SA) inspired from annealing in metallurgy. These three nature inspired search techniques are used to find the longest snake in 8-dimensional hypercube. Different snake representations (Node Sequence, Transition Sequence and Bit Representations), various parameter settings and aspects like engineered conditioning are used for each technique in an effort to find the longest snake possible. This project found snakes of length 97 using SA and GA techniques. The longest snake found using the PSO technique is of length 95.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectSnake-in-the-box
dc.subjectGenetic Algorithm
dc.subjectParticle Swarm Optimization
dc.subjectSimulated Annealing
dc.subjectNature inspired search strategies
dc.subjectNode sequence representation
dc.subjectTransition sequence representation
dc.subjectBit representation
dc.titleSnake-in-the-box problem using nature inspired search
dc.typeThesis
dc.description.degreeMS
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorWalter D. Potter
dc.description.committeeWalter D. Potter
dc.description.committeeKhaled Rasheed
dc.description.committeeTianming Liu


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