{"id":{"repo_id":"must-thes","oai_identifier":"oai:scholarsmine.mst.edu:doctoral_dissertations-2746"},"canonical_url":"https://search.dev.ndltd.org/etd/must-thes/oai:scholarsmine.mst.edu:doctoral_dissertations-2746","repository":{"repo_id":"must-thes","name":"Missouri University of Science and Technology","base_url":"https://scholarsmine.mst.edu/do/oai/"},"display":{"title":"The stored non-domination level multi-objective evolutionary algorithm","abstract":"\"The research presented in this dissertation is in the field of Multi-Objective Evolutionary Algorithms. Evolutionary Algorithms (EAs) are a class of algorithms which model Darwin's theory of evolution to search for solutions to difficult problems. Multi-Objective Evolutionary Algorithms (MOEAs) are a broader case of the standard EA. The primary distinction between an EA and a MOEA is that and EA searches for a single solution based on one objective, while a MOEA searches for a set of solutions based on a number of different objectives. The heart of this research is a new algorithm call SNDL-MOEA, which stands for \"Stored Non-Domination Level Multi-Objective Evolutionary Algorithm\"--Abstract, page iii.","abstract_html":""The research presented in this dissertation is in the field of Multi-Objective Evolutionary Algorithms. Evolutionary Algorithms (EAs) are a class of algorithms which model Darwin's theory of evolution to search for solutions to difficult problems. Multi-Objective Evolutionary Algorithms (MOEAs) are a broader case of the standard EA. The primary distinction between an EA and a MOEA is that and EA searches for a single solution based on one objective, while a MOEA searches for a set of solutions based on a number of different objectives. The heart of this research is a new algorithm call SNDL-MOEA, which stands for "Stored Non-Domination Level Multi-Objective Evolutionary Algorithm"--Abstract, page iii.","abstract_has_math":false,"creators":["Johnson, Matt D."],"institution":"University of Missouri--Rolla","degree_name":"Ph. 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