TY - GEN
T1 - Multiple-attribute decision making with interactive estimation of user preference
AU - Murata, Junichi
AU - Kitahara, Kentaro
PY - 2010
Y1 - 2010
N2 - The aim of multi-objective optimization or multiple-attribute decision making is to find the most appropriate solution among Pareto solutions. Usually, decision makers are in charge of evaluating and rating objective functions or attributes. However, in a good number of practical decision making problems especially in the area of public services e.g. determining the service contents of public transport, the decision makers determine the service contents while the users evaluates the quality of the service. In these problems where decision makers and evaluators are different, an effective method is necessary that can estimate the preferences of the evaluators (users). In the paper, an interactive method is proposed that estimates or learns the user preferences and finds the solution based on the estimated results.
AB - The aim of multi-objective optimization or multiple-attribute decision making is to find the most appropriate solution among Pareto solutions. Usually, decision makers are in charge of evaluating and rating objective functions or attributes. However, in a good number of practical decision making problems especially in the area of public services e.g. determining the service contents of public transport, the decision makers determine the service contents while the users evaluates the quality of the service. In these problems where decision makers and evaluators are different, an effective method is necessary that can estimate the preferences of the evaluators (users). In the paper, an interactive method is proposed that estimates or learns the user preferences and finds the solution based on the estimated results.
UR - http://www.scopus.com/inward/record.url?scp=77954597653&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954597653&partnerID=8YFLogxK
U2 - 10.2316/p.2010.674-033
DO - 10.2316/p.2010.674-033
M3 - Conference contribution
AN - SCOPUS:77954597653
SN - 9780889868182
T3 - Proceedings of the 10th IASTED International Conference on Artificial Intelligence and Applications, AIA 2010
SP - 43
EP - 49
BT - Proceedings of the 10th IASTED International Conference on Artificial Intelligence and Applications, AIA 2010
PB - ACTA Press
T2 - 10th IASTED International Conference on Artificial Intelligence and Applications, AIA 2010
Y2 - 15 February 2010 through 17 February 2010
ER -