Title :
Preference Incorporation in Multi-objective Evolutionary Algorithms: A Survey
Author :
Rachmawati, L. ; Srinivasan, Dipti
Author_Institution :
Nat. Univ. of Singapore, Singapore
Abstract :
This 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 decisionmaking. 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.
Keywords :
Pareto optimisation; decision making; evolutionary computation; Pareto-optimality criterion; decisionmaking; evolutionary multiobjective optimization; human preference; multiobjective evolutionary algorithms; preference incorporation; problem knowledge; Constraint optimization; Decision feedback equalizers; Decision making; Displays; Drives; Evolutionary computation; Humans; Uncertainty; Utility theory;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688414