TY - GEN
T1 - Composite fuzzy measure and its application to automobile factory investment decision making
AU - Kaino, Toshihiro
AU - Hirota, Kaoru
N1 - Publisher Copyright:
© 2001 IEEE.
PY - 2001
Y1 - 2001
N2 - In the application using fuzzy measure (on a real number), it is a problem how to evaluate the inbetween intervals each of which is characterized by a fuzzy measure. Especially, when the differentiation of the Choquet integral is applied to the real world problem, this is essentially important So, a composite fuzzy measure built up from fuzzy measures defined on fuzzy measurable spaces has been proposed using composite fuzzy weights by Kaino and Hirota. Here, the measurable space of this composite fuzzy measure is the direct sum of measurable spaces. Moreover, an associative, composite fuzzy measure built up from three fuzzy measures has also been proposed. But, it is practically required that the fuzzy measure should be composed by plural fuzzy measures. Here, the associative, composite fuzzy measure built up from three fuzzy measures is recursively extended to an associative, composite fuzzy measure built up from a finite number of fuzzy measures. As an application, it is applied to the automobile factory capital investment decision making problem. It is assumed that an automobile company has a sales plan of a new car. The current factory line has a capacity to manufacture 3,200 new cars, additional to the current car lines. Then, by the use of this composite fuzzy measure, the differentiation of the Choquet integral becomes the important index for decision making, which is confirmed by this decision making experiment.
AB - In the application using fuzzy measure (on a real number), it is a problem how to evaluate the inbetween intervals each of which is characterized by a fuzzy measure. Especially, when the differentiation of the Choquet integral is applied to the real world problem, this is essentially important So, a composite fuzzy measure built up from fuzzy measures defined on fuzzy measurable spaces has been proposed using composite fuzzy weights by Kaino and Hirota. Here, the measurable space of this composite fuzzy measure is the direct sum of measurable spaces. Moreover, an associative, composite fuzzy measure built up from three fuzzy measures has also been proposed. But, it is practically required that the fuzzy measure should be composed by plural fuzzy measures. Here, the associative, composite fuzzy measure built up from three fuzzy measures is recursively extended to an associative, composite fuzzy measure built up from a finite number of fuzzy measures. As an application, it is applied to the automobile factory capital investment decision making problem. It is assumed that an automobile company has a sales plan of a new car. The current factory line has a capacity to manufacture 3,200 new cars, additional to the current car lines. Then, by the use of this composite fuzzy measure, the differentiation of the Choquet integral becomes the important index for decision making, which is confirmed by this decision making experiment.
UR - http://www.scopus.com/inward/record.url?scp=84949234134&partnerID=8YFLogxK
U2 - 10.1109/CIRA.2001.1013209
DO - 10.1109/CIRA.2001.1013209
M3 - Conference contribution
AN - SCOPUS:84949234134
T3 - Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
SP - 272
EP - 276
BT - Proceedings - 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation
A2 - Zhang, Hong
A2 - Liu, Peter Xiaoping
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2001
Y2 - 29 July 2001 through 1 August 2001
ER -