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dc.contributor.authorBrooks, Philip
dc.date.accessioned2014-03-04T18:58:36Z
dc.date.available2014-03-04T18:58:36Z
dc.date.issued2010-12
dc.identifier.otherbrooks_philip_201012_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/brooks_philip_201012_ms
dc.identifier.urihttp://hdl.handle.net/10724/26858
dc.description.abstractIn this thesis I examine the poor performance of Discrete Particle Swarm Optimization when applied to forest planning, an optimization problem in which the goal is to maintain an even flow of timber from a forested area. I consider an alternative priority representation that encodes a permutation or ordering of plan elements in real numbers to improve the handling of constraints. I also examine its applications to two other constrained optimization problems, n-queens and snake-in-a-box, in order to show how it handles different kinds of problems. I find that priority representation is a useful tool for optimization within constraints.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectParticle swarm optimization
dc.subjectPriority representation
dc.subjectForest planning
dc.subjectN queens
dc.subjectSnake-in-a-box
dc.subjectPermutation representation
dc.titleParticle Swarm Optimization and priority representation
dc.typeThesis
dc.description.degreeMS
dc.description.departmentArtificial Intelligence Center
dc.description.majorArtificial Intelligence
dc.description.advisorWalter D. Potter
dc.description.committeeWalter D. Potter
dc.description.committeeKhaled Rasheed
dc.description.committeePete Bettinger


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