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Fuzzy Linear Programming in Real-World Applications: A Comparative Study of Agricultural and Financial Optimization |
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PP: 849-862 |
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doi:10.18576/amis/190411
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Author(s) |
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Khaleel Ibrahim Al-Daoud,
Yogeesh N,
Suleiman Ibrahim Shelash Mohammad,
N. Raja,
F. T. Z. Jabeen,
P. William,
Asokan Vasudevan,
Mohammad Faleh Ahmmad Hunitie,
Nawaf Alshdaifat,
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Abstract |
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| It’s called a Fuzzy Linear Programming (FLP), which is a robust optimization method to address uncertainty in real life decision-making problems. In this study, we investigate the use of FLP in two separate case studies pertaining to agricultural production optimization and investment portfolio management. The first case study utilizes FLP to support optimal allocation of land and water resources for crop production under uncertain market prices and crop resource requirements for wheat and corn. In our second case study, we take a look at the optimization of an investment portfolio during an uncertain market, where the returns and risks associated with stocks, bonds, and real estate are modelled as fuzzy numbers. Each case study applies defuzzification methods, which transform fuzzy values into real-number quantification (centroid and mean of maxima methods). FLP is adopted to deal with the uncertainty, and both the Simplex method and evolutionary algorithms are used to solve the optimization problems. The outcomes from both case studies illustrate that FLP can yield powerful solutions to complex optimization challenges in agriculture and finance, which can serve as a foundation for understanding the cross-environmental applicability of fuzzy logic across various sectors including energy, manufacturing, and healthcare.
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