Please use this identifier to cite or link to this item:
DC FieldValue
dc.titlePreference incorporation in multi-objective evolutionary algorithms: A survey
dc.contributor.authorRachmawati, L.
dc.contributor.authorSrinivasan, D.
dc.identifier.citationRachmawati, L.,Srinivasan, D. (2006). Preference incorporation in multi-objective evolutionary algorithms: A survey. 2006 IEEE Congress on Evolutionary Computation, CEC 2006 : 962-968. ScholarBank@NUS Repository.
dc.description.abstractThis paper presents a review of preference incorporation in Multi-Objective Evolutionary Algorithms (MOEA). The incorporation of preference in Evolutionary Multi-objective Optimization (EMO) promotes better decision-making. Introducing preference in MOEAs increases the specificity of selection, leading to solutions which are of higher relevance to the Decision Maker(s). When many objectives are involved, a MOEA based on pure Pareto-optimality criterion may not achieve meaningful search. The incorporation of preference addresses this concern. The incorporation of preference is difficult because of uncertainties arising from lack of prior problem knowledge and fuzziness of human preference. Further, decision making is a complex and ill-defined process which at times could not be mathematically characterized. These concerns must be addressed in the incorporation of preference. © 2006 IEEE.
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitle2006 IEEE Congress on Evolutionary Computation, CEC 2006
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.