TY  - JOUR
ID  - scholars10659
N1  - cited By 1; Conference of 1st International Conference on the Computer Science and Engineering, COMPSE 2016 ; Conference Date: 11 November 2016 Through 12 November 2016; Conference Code:252929
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079148145&doi=10.1007%2f978-3-319-66984-7_13&partnerID=40&md5=258427d126d4c85fbba2be7cfaf0956c
A1  - Arbaiy, N.
A1  - Samsudin, N.A.
A1  - Mustapa, A.
A1  - Watada, J.
A1  - Lin, P.-C.
EP  - 235
N2  - Mathematical models are established to represent real-world problems. Since the real-world faces various types of uncertainties, it makes mathematical model suffers with insufficient uncertainties modeling. The existing models lack of explanation in dealing uncertainties. In this paper, construction of mathematical model for decision making scenario with uncertainties is presented. Primarily, fuzzy random regression is applied to formulate a corresponding mathematical model from real application of a multi-objective problem. Then, a technique in possibilistic theory, known as modality optimization is used to solve the developed model. Consequently, the result shows that a well-defined multi-objective mathematical model is possible to be formulated for decision making problems with the uncertainty. Indeed, such problems with uncertainties can be solved efficiently with the presence of modality optimization. © Springer International Publishing AG 2018.
SN  - 1860949X
TI  - An enhanced possibilistic programming model with fuzzy random confidence-interval for multi-objective problem
Y1  - 2018///
VL  - 741
PB  - Springer Science and Business Media Deutschland GmbH
SP  - 217
AV  - none
JF  - Studies in Computational Intelligence
ER  -