TY - JOUR
T1 - Using Choquet integral as preference model in interactive evolutionary multiobjective optimization
AU - Branke, Juergen
AU - Corrente, Salvatore
AU - Greco, Salvatore
AU - Słowiński, Roman
AU - Zielniewicz, Piotr
N1 - Publication state chronology
One or more publication states have been input in an unexpected chronology. Found [Published: 1 May 2016] -> [Accepted/In press: 15 Oct 2015] date ordering, but expected [Accepted/In press] -> [Published] chronology
EMBARGO 24 MTHS
NOTICE: this is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 250(3), (May 2016), DOI: 10.1016/j.ejor.2015.10.027
PY - 2016/5/1
Y1 - 2016/5/1
N2 - We propose an interactive multiobjective evolutionary algorithm that attempts to discover the most preferred part of the Pareto-optimal set. Preference information is elicited by asking the user to compare some solutions pairwise. This information is then used to curb the set of compatible user’s value functions, and the multiobjective evolutionary algorithm is run to simultaneously search for all solutions that could potentially be the most preferred. Compared to previous similar approaches, we implement a much more efficient way of determining potentially preferred solutions, that is, solutions that are best for at least one value function compatible with the preference information provided by the decision maker. For the first time in the context of evolutionary computation, we apply the Choquet integral as a user’s preference model, allowing us to capture interactions between objectives. As there is a trade-off between the flexibility of the value function model and the complexity of learning a faithful model of user’s preferences, we propose to start the interactive process with a simple linear model but then to switch to the Choquet integral as soon as the preference information can no longer be represented using the linear model. An experimental analysis demonstrates the effectiveness of the approach.
AB - We propose an interactive multiobjective evolutionary algorithm that attempts to discover the most preferred part of the Pareto-optimal set. Preference information is elicited by asking the user to compare some solutions pairwise. This information is then used to curb the set of compatible user’s value functions, and the multiobjective evolutionary algorithm is run to simultaneously search for all solutions that could potentially be the most preferred. Compared to previous similar approaches, we implement a much more efficient way of determining potentially preferred solutions, that is, solutions that are best for at least one value function compatible with the preference information provided by the decision maker. For the first time in the context of evolutionary computation, we apply the Choquet integral as a user’s preference model, allowing us to capture interactions between objectives. As there is a trade-off between the flexibility of the value function model and the complexity of learning a faithful model of user’s preferences, we propose to start the interactive process with a simple linear model but then to switch to the Choquet integral as soon as the preference information can no longer be represented using the linear model. An experimental analysis demonstrates the effectiveness of the approach.
KW - Multiobjective optimization
KW - Evolutionary algorithms
KW - Interaction between criteria
KW - Choquet integral
U2 - 10.1016/j.ejor.2015.10.027
DO - 10.1016/j.ejor.2015.10.027
M3 - Article
SN - 0377-2217
VL - 250
SP - 884
EP - 901
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 3
ER -