Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486190
Title: Combination of Evolutionary Algorithms with Decomposition Techniques for Multiobjective Optimization
Author: Li, Hui
Awarding Body: University of Essex
Current Institution: The University of Essex pre-October 2008
Date of Award: 2008
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Abstract:
Multiobjective optimization problems (MOPs) arise in many real-life applications. In recent years, multiobjective evolutionary algorithms (MOEAs) have attracted a growing attention since they are able to find multiple compromise solutions (known as Pareto-optimal solutions) in a single run. Decomposition (i.e., the use of multiple aggregation functions) is one of the basic strategies for fitness assignment in MOEAs. However, the advantages of decomposition techniques have not been fully utilized in Ivl0EAs. This thesis mainly studies the combination of evolutionary algorithms with decomposition techniques for multiobjective optimization.
Supervisor: Not available Sponsor: Not available
Qualification Name: University of Essex, 2008 Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.486190  DOI: Not available
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