Please use this identifier to cite or link to this item: https://doi.org/10.1109/CEC.2010.5586413
Title: Incorporation of imprecise goal vectors into evolutionary multi-objective optimization
Authors: Rachmawati, L.
Srinivasan, D. 
Issue Date: 2010
Source: 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
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