Implementation of Fuzzy Linear Programming Approach for More Accurate Demand Forecasting in a Make-to-Stock Company

Abstract

Demand forecasting is of crucial importance for make-to-stock companies because product demand is uncertain and it changes with time. Fuzzy linear programming (FLP) can be an optimum approach for such uncertain situations. In this study, the FLP model was used for more accurate demand forecasting in a make-to-stock company. Demand forecasting study was carried out according to the FLP method and linear programming (LP) method. Solutions of FLP and LP were compared in terms of imputed shortage cost, inventory carrying cost, and net profit. Results show that the applied FLP method is more advantageous than LP as it provides a 67% decrease in costs and a 15% increase in net profit.

Keywords

• Demand Forecasting
• Fuzzy Linear Programming
• Make-to-Stock

References

1. [1] S. M. Guu and Y. K. Wu, "Two-phase approach for solving the fuzzy linear programming problems", Fuzzy Sets and Systems, vol. 107, pp. 191-195, 1999.
2. [2] A. N. Gani, C. Duraisamy, and C. Veeramani, "A note on fuzzy linear programming problem using L-R fuzzy number", International Journal of Algorithms, Computing and Mathematics, vol. 3, pp. 93-106, 2009.
3. [3] A. Azizi, A. Y. Ali, and L. W. Ping, "Modelling production uncertainties using the adaptive neuro-fuzzy inference system", South African Journal of Industrial Engineering, vol. 26, no. 1, pp. 224-234, 2015.
4. [4] K. Worapradya and P. Thanakijkasem, "Optimising steel production schedules via a hierarchical genetic algorithm", South African Journal of Industrial Engineering, vol. 25, no. 2, pp. 209-221, 2014.
5. [5] J. C. Figueroa-García, D. Kalenatic, and C. A. Lopez-Bello, "Multi-period mixed production planning with uncertain demands: fuzzy and interval fuzzy sets approach", Fuzzy Sets and Systems, vol. 206, pp. 21-38, 2012.
6. [6] S. A. Torabi, M. Ebadian, and R. Tanha, "Fuzzy hierarchical production planning (with a case study)", Fuzzy Sets and Systems, vol. 161, no. 11, pp. 1511-1529, 2010.
7. [7] B. Bilgen, "Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem", Expert Systems with Applications, vol. 37, no. 6, pp. 4488-4495, 2010.
8. [8] I. Ertuğrul and A. Tuş, "Interactive fuzzy linear programming and an application sample at a textile firm", Fuzzy Optimization and Decision Making, vol. 6, no. 1, pp. 29-49, 2007.

9. [9] S. Akbaş, T. E. Dalkilic, and T. G. Aksoy, "A study on portfolio selection based on fuzzy linear programming", International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 30, no. 2, pp. 211-230, 2022.
10. [10] D. Yin, "Application of interval valued fuzzy linear programming for stock portfolio optimization", Applied Mathematics, vol. 9, pp.101-113, 2018.
11. [11] Ş. Emeç and G. Akkaya, "Developing a new optimization energy model using fuzzy linear programming", Journal of Intelligent and Fuzzy Systems, vol. 40, pp. 9529–9542, 2021.
12. [12] P. Sefeedpari, S. Rafiee, M. Sharifi, and A. Akram, "Detecting the best optimal dairy cattle herd sizes based on energy consumption using fuzzy linear programming model", Iranian Journal of Biosystem Engineering, vol. 49, no. 1, pp. 149-159, 2018.
13. [13] I. U. Khan, and F. Rafique, "Minimum-cost capacitated fuzzy network, fuzzy linear programming formulation, and perspective data analytics to minimize the operations cost of American airlines", Soft Computing, vol. 25, pp. 1411–1429, 2021.
14. [14] E. Escobar-Gómez, J. L. Camas-Anzueto, S. Velázquez-Trujillo, H. Hernández-de-León, R. Grajales-Coutiño, E. Chandomí-Castellanos, and H. Guerra-Crespo, "A linear programming model with fuzzy arc for route optimization in the urban road network", Sustainability, vol. 11, no. 23, pp. 6665, 2019.
15. [15] A. Güler and H. Bircan, "Fuzzy linear programming and an application in BIMS production facility", Turkish Studies - Economy, vol. 16, no. 2, pp. 823-837, 2021.
16. [16] G. Chen and T. T. Pham, Introduction to Fuzzy Sets, Fuzzy Logic and Fuzzy Control Systems. Boca Raton: CRC Press, 2001.
17. [17] B. Yıldız, Artificial Intelligence in Financial Analysis, Detay Publishing, 2009.
18. [18] M. Mutingi and C. Mbohwa, "A fuzzy-based particle swarm optimisation approach for task assignment in home healthcare", South African Journal of Industrial Engineering, vol. 25, no. 3, pp. 84-95, 2014.
19. [19] E. Dervişoğlu, "Fuzzy linear programming: review and implementation", Master thesis, Sabanci University Institute of Engineering and Science, Istanbul, 2005.
20. [20] J. L. Verdegay, "Progress on fuzzy mathematical programming: A personal perspective", Fuzzy Sets and Systems, vol. 281, pp. 219-226, 2015.
21. [21] C. S. Lee and C. G. Wen, "River assimilative capacity analysis via fuzzy linear programming", Fuzzy Sets and Systems, vol. 79, pp. 191-201, 1996.
22. [22] J. Ren and T. B. Sheridan, Optimization with Fuzzy Linear Programming and Fuzzy Knowledge Base, IEEE 3rd International Fuzzy Systems Conference, pp. 1389-1393, Orlando, 1994.
23. [23] R. R. Gasimov and K. Yenilmez, "Solving fuzzy linear programming problems with linear membership functions", Turkish Journal of Mathematics, vol. 26, no. 4, pp. 375-396, 2002.