Fuzzy random regression to improve coefficient estimation for Malaysian Agricultural Industry
Conventional model setting of production planning is developed with numerical crisp values. Additionally coefficient values must be determined before the model is set. It is however troublesome and complex for decision maker to provide rigid values and determining the coefficient values for th...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/1475/1/24p%20HAMIJAH%20MOHD%20RAHMAN.pdf http://eprints.uthm.edu.my/1475/2/HAMIJAH%20MOHD%20RAHMAN%20WATERMARK.pdf |
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| Summary: | Conventional model setting of production planning is developed with numerical crisp
values. Additionally coefficient values must be determined before the model is set. It
is however troublesome and complex for decision maker to provide rigid values and
determining the coefficient values for the model. Building the production planning
model with precise values sometimes generates improper solution. Hence, this study
proposes a fuzzy random regression method to estimate the coefficient values for
which statistical data contains simultaneous fuzzy random information. A numerical
example illustrates the proposed solution approach whereby coefficient values are
successfully deduce from the statistical data and the fuzziness and randomness were
treated based on the property of fuzzy random regression. The implementation of the
fuzzy random regression method shows the significant capabilities to estimate the
coefficient value to further improve the model setting of production planning
problem which retain the simultaneous uncertainties. |
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