Hybrid Uncertainties Modeling for Production Planning Problems

Authors

  • Hamijah Mohd. Rahman Soft Computing and Data Mining Centre, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn, Parit Raja 86400 Batu Pahat, Johor
  • Nureize Arbaiy Soft Computing and Data Mining Centre, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn, Parit Raja 86400 Batu Pahat, Johor
  • Pei-Chun Lin Department of Information Engineering and Computer Science, Feng Chia University, No. 100, Wenhwa Rd., Seatwen, Taichung, Taiwan 40724

DOI:

https://doi.org/10.26713/cma.v8i2.709

Keywords:

Production planning, Coefficient estimation, Hybrid uncertainties, Fuzzy random variable, Fuzzy random regression

Abstract

The formulated mathematical model needs pre-determined and precise model parametersto find a solution. However, the model parameters such as coefficient value are usually not precisely known. Coefficient plays a pivotal role sincethe coefficientcouldprovide important information in relationship between algebraic and linguistic expression. Existing method which is commonly used to generate the precise parametric valuesis unable to handle the coexistence of fuzzy information. Moreover, selecting real numbers for coefficients in random process increases the complexity inprogramming process. Hence, we proposed a fuzzy random regression method in this paper to estimate the precise coefficient values which contains fuzzy random information. An illustrative numerical example is provided to deduce coefficient values from different data representation which included the fuzziness and randomness.The coefficients were treated based on the property of fuzzy random regression. The approach results show that we have the significant capabilities to estimate the coefficient value and improve the model which retain the simultaneous uncertainties and set up in production planning problem.

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Published

30-08-2017
CITATION

How to Cite

Rahman, H. M., Arbaiy, N., & Lin, P.-C. (2017). Hybrid Uncertainties Modeling for Production Planning Problems. Communications in Mathematics and Applications, 8(2), 191–206. https://doi.org/10.26713/cma.v8i2.709

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Section

Research Article