Hybrid Uncertainties Modeling for Production Planning Problems
S. Abdollahzadeh, M. Rezaei, M. Dabbaghian and A. Norouzi, A goal programming model for computation of fuzzy linear regression with least error, in: Computer Engineering and Technology (ICCET), 2010 2nd International Conference on, 493 (2010).
F. Denisa, Bottleneck management in discrete batch production, Journal of Competitiveness 4 (2) (2012), 161 – 171.
G. González-Rodríguez, Á. Blanco, A. Colubi and M.A. Lubiano, Estimation of a simple linear regression model for fuzzy random variables, Fuzzy Sets and Systems 160 (3) (2009), 357 – 370.
S.C. Graves, Manufacturing planning and control, in: Handbook of Applied Optimization, Oxford University Press, 728 – 746 (1999).
H. Kwakernaak, Fuzzy random variables – I, Definitions and theorems, Information Sciences 15 (1) (1978), 1 – 29.
P.-C. Lin, J. Watada and B. Wu, A parametric assessment approach to solving facility location problems with fuzzy demands, IEEJ Transactions on Electronics, Information and Systems 9 (5)
(2014), 484 – 493.
P.-C. Lin, J. Watada and B. Wu, Risk assessment of a portfolio selection model based on a fuzzy statistical test, IEICE Transactions on Information and Systems E96-D (3) (2013), 579 – 588.
Malaysian Investment Development Authority, Rubber-based industry, retrieved on October 10, 2013 from http://www.mida.gov.my
Malaysian Rubber Board, Natural Rubber Statistic, retrieved September 1, 2013 from http: //www.lgm.gov.my
Malaysian Rubber Export Promotion Council, Rubber Statistical Bulletin, retrieved on October 10, 2013 from http://www.mrepc.gov.my
Market Watch 2012, The Rubber Sector in Malaysia, retrieved October 22, 2013 from http://www.malaysia.ahk.de
A. Messac, W.M. Batayneh and A. Ismail-Yahaya, Production planning optimization with physical programming, Engineering Optimization 34 (4) (2002), 323 – 340.
D.C. Montgomery, E.A. Peck and G.G. Vining, Introduction to Linear Regression Analysis, 821, Wiley (2012).
W. Näther, Regression with fuzzy random data, Computational Statistics & Data Analysis 51 (1) (2006), 235 – 252.
A. Nureize and J. Watada and S. Wang, Fuzzy random regression based multi-attribute evaluation and its application to oil palm fruit grading, Annals of Operations Research 219 (1) (2014), 299 – 315.
A. Nureize and J. Watada, A fuzzy regression approach to a hierarchical evaluation model for oil palm fruit grading, Fuzzy Optimization and Decision Making 9 (1) (2010), 105 – 122.
A. Nureize and J. Watada, Multi-level multi-objective decision problem through fuzzy random regression based objective function, in: Fuzzy Systems (FUZZ), 2011 IEEE International Conference
on IEEE (2011).
A.G. Sarip, B.H. Muhammad and M.N. Daud, Application of fuzzy regression model for real estate price prediction, Malaysian Journal of Computer Science 29 (1) (2016), 15 – 27.
A.F. Shapiro, Fuzzy Regression Models, Article of Penn State University (2005).
H. Tanaka, H. Isao and J. Watada, Possibilistic linear regression analysis for fuzzy data, European Journal of Operational Research 40 (3) (1989), 389 – 396.
S.A. Torabi, M. Ebadian and R. Tanha, Fuzzy hierarchical production planning (with a case study), Fuzzy Sets and Systems 161 (11) (2010), 1511 – 1529.
J. Watada, Building models based on environment with hybrid uncertainty, in: Modeling, Simulation and Applied Optimization (ICMSAO), 2011, 4th International Conference on. IEEE (2011).
J. Watada, S. Wang and W. Pedrycz, Building confidence-interval-based fuzzy random regression models, Fuzzy Systems, IEEE Transactions on 17 (6) (2009), 1273 – 1283.
M.S. Yang and C.H. Ko, On cluster-wise fuzzy regression analysis, Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 27 (1) (1997), 1 – 13.
- There are currently no refbacks.
eISSN 0975-8607; pISSN 0976-5905