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|Title:||Incorporation of imprecise goal vectors into evolutionary multi-objective optimization||Authors:||Rachmawati, L.
|Issue Date:||2010||Citation:||Rachmawati, L.,Srinivasan, D. (2010). Incorporation of imprecise goal vectors into evolutionary multi-objective optimization. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/CEC.2010.5586413||Abstract:||Preference-based techniques in multi-objective evolutionary algorithms (MOEA) are gaining importance. This paper presents a method of representing, eliciting and integrating decision making preference expressed as a set of imprecise goal vectors into a MOEA with steady-state replacement. The specification of a precise goal vector without extensive knowledge of problem behavior often leads to undesirable results. The approach proposed in this paper facilitates the linguistic specification of goal vectors relative to extreme, non-dominated solutions (i.e. the goal is specified as "Very Small", "Small", "Medium", "Large", and "Very Large") with three degrees of imprecision as desired by the decision maker. The degree of imprecision corresponds to the density of solutions desired within the target subset. Empirical investigations of the proposed method yield promising results. © 2010 IEEE.||Source Title:||2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010||URI:||http://scholarbank.nus.edu.sg/handle/10635/70578||ISBN:||9781424469109||DOI:||10.1109/CEC.2010.5586413|
|Appears in Collections:||Staff Publications|
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