Implementation of Genetic Algorithms and Parallel Simulated Annealing in OCEON-P

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dc.contributor.advisor Paul Turinsky, Committee Chair en_US
dc.contributor.advisor Dmitriy Anistratov, Committee Member en_US
dc.contributor.advisor Moody Chu, Committee Member en_US
dc.contributor.author Du, Shuang en_US
dc.date.accessioned 2010-04-02T17:55:07Z
dc.date.available 2010-04-02T17:55:07Z
dc.date.issued 2008-11-03 en_US
dc.identifier.other etd-10222008-141121 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/396
dc.description.abstract OCEON-P is a computer program whose purpose is to minimize the levelized fuel cycle cost over a multi-cycle planning horizon. It integrates a core simulator, fuel cycle cost calculator and mathematical optimization engine. The accuracy of the predicted fuel cycle cost, whose minimization guides the optimization of the decision variables, is directly related to the fidelity of the reactor core simulator used by the program. Unfortunately, high fidelity core simulators also require longer run times. To improve these run times, this project sought to parallelize the optimization process so that multiple processors may share the computational burden. In addition, an effort was made to reduce the number of fuel cycles that must be examined to complete the optimization, which also reduces the computer run times. Parallelization of the process was introduced by the replacement of the current serial simulated annealing method with parallel simulated and genetic algorithms. It was hoped that genetic algorithms would also reduce the number of fuel cycles that must be examined during the optimization search. However, it was found that although genetic algorithms could find the same caliber of best solutions as simulated annealing, simulated annealing could produce a better family of acceptable solutions. Furthermore, parallel simulated annealing was able to reproduce the same quality and robustness of serial simulated annealing while decreasing run times significantly through use of multiple processors. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject optimization en_US
dc.subject genetic algorithms en_US
dc.subject simulated annealing en_US
dc.subject nuclear fuel cycle en_US
dc.title Implementation of Genetic Algorithms and Parallel Simulated Annealing in OCEON-P en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Nuclear Engineering en_US


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