Fuzzy Multi-objective Production Distribution Planning by Considering CO2 Emission Cost and Solving by a Novel Fuzzy Multi-choice Goal Programming

Document Type : Original Article

Authors

1 Associate Professor, Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.

2 Ph.D Students, Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.

Abstract

In today's competitive world, companies need to effectively manage their supply chains in changing market conditions, and they are also obliged to compensate for their environmental damages. In this research, a two-echelon multi-product multi-period supply chain network with production and distribution centers has been modeled with three objectives: minimizing logistic costs, delivery time, and CO2 emission costs. Customer demand parameters, available levels of human and machinery resources are uncertain and considered as fuzzy numbers. Additionally, the possibility of using subcontracting services for production and transportation operations at a higher cost exists. The main innovation of this research is modeling the possibility of using different transportation systems and considering their pollution, and using a novel fuzzy multi-criteria goal programming method (proposed in 2018) for solving the problem. Real data from "Daya Technology" company has also been used for case study and model evaluation.

Keywords

Main Subjects

References

  1. Amiri, M., Barzegar, M., & Niknamfar, A. (2016). A Robust Optimization Approach for an Integrated Production Distribution Planning in a Supply Chain. The Journal of Industrial Management Perspective, 6(3), 9-28. (In Persian)
  2. Badhotiya, G.K., Soni, G. & Mittal, M.L. (2019). Fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain.International Journal of Advanced Manufacturing Technology, 102, 635–645.
  3. Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17, 141–164.
  4. Ben Abid, T., Ayadi, O., & Masmoudi, F. (2020). An integrated production-distribution planning problem under demand and production capacity uncertainties: new formulation and case study. Mathematical Problems in Engineering, 1, 1-15.
  5. Chung, C.K., Chen, H.M., Chang, C.T., & Hau-Lieng Huang, H.L. (2018). On fuzzy multiple objective linear programming problems. Expert Systems with Applications, 114, 552-562.
  6. Goodarzian, F., & Hosseini-Nasab, H. (2021). Applying a fuzzy multi-objective model for a production-distribution network design problem by using a novel self-adoptive evolutionary algorithm. International Journal of Systems Science: Operations & Logistics, 8(1), 1-22.
  7. Goodarzian, F., Shishebori, D., Nasseriand, H., & Dadvar, F. (2021). A bi-objective production-distribution problem in a supply chain network under grey flexible conditions. RAIRO Operations Research, 55, 1287-1316.
  8. Guu, S.M., & Wu, Y.K. (1999). Weight coefficients in two-phase approach for solving the multiple objective programming problems. Fuzzy Sets and Systems, 85, 45-48.
  9. Guu, S.M., & Wu, Y.K. (1999). Two-phase approach for solving the fuzzy linear programming problems. Fuzzy Sets and Systems, 107, 191-195.
  10. Hannan, E. L. (1981). Linear programming with multiple fuzzy goals. Fuzzy Sets and Systems, 6, 235–248.
  11. Lai, Y. J., & Hwang, C. L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49, 121–133.
  12. Liang, T.F. (2008a). Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain. Computers and Industrial Engineering, 55(3), 676–694.
  13. Liang, T.F. (2008b). Integrating production-transportation planning decision with fuzzy multiple goals in supply chains. International Journal of Production Research, 46(6), 1477–1494, (2008b).
  14. Liang, T.F. (2012). Integrated manufacturing/distribution planning decisions with multiple imprecise goals in an uncertain environment. Quality and Quantity, 46, 137-153.
  15. Mohammed, A., & Wang, Q. (2017). The fuzzy multi-objective distribution planner for a green meat supply chain. Int J Prod Econ, 184, 47–58.
  16. Mohammadi, M., & Soleimani, H. (2020). Investigating Open Loop and Closed-Loop Supply Chain under Uncertainty (Case Study: Iran Teransfo Company). The Journal of Industrial Management Perspective, 10(2), 33-53. (In Persian)
  17. Moon, I., Jeong, Y. J., & Saha, S. (2016). Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint. Sustainability, 8(8), 798-811.
  18. Mousakhani, S., & Sangari, M.S. (2020). An integrated location-production-distribution model in the green supply chain considering customer service level. Industrial Management Studies, 18(56), 275- 304.
  19. Nobil, A.H., Kazemi, A. (2016). Presenting a fuzzy multi-objective model for integrated production-distribution planning in a four-echelon closed-loop supply chain. International Journal of Industrial Engineering & Production Management, 27(1), 91-104. (In Persian)
  20. Pathak, S., & Sarkar, S. (2011). A fuzzy optimization model to the aggregate production/distribution planning decision in a multi-item supply chain network. International Journal of Management Science and Engineering Management, 6(1), 163-173.
  21. Peidro, D., Mula, J., Alemany, M.M.E., & Lario, F.-C. (2012). Fuzzy multi-objective optimisation for master planning in a ceramic supply chain. International Journal of Production Research, 50, 3011-3020.
  22. Raad, A., Sadeghi, A., & Ghasemi, B. (2016). Mathematical Modeling of Two-Echelon with Multiple Manufacturers and Transportation in the Supply Chain. The Journal of Industrial Management Perspective, 6(3), 77-100. (In Persian)
  23. Ramik, J., & Rimanek, J. (1985). Inequality relation between fuzzy numbers and its use in fuzzy optimization. Fuzzy Sets and Systems, 16, 123–138.
  24. Rommelfanger, H. (1996). Fuzzy linear programming and applications. European Journal of Operational Research, 92, 512–527.
  25. Sajedi, S., Sarfaraz, A., Bamdad, S., & Khalili-Damghani, K. (2021). Mathematical model of location, multi-commodity and multi-period in sustainable closed-loop supply chain considering risk and demand and quality uncertainty (A case Study). Journal of Industrial Management Perspective, 11(2), 271-304. (In Persian)
  26. Sharahi, S., Khalili-Damghani, K., Abtahi, A.R., & Rashidi-Komijan, A. (2018). Type-II fuzzy multi-product, multi-level, multi-period location–allocation, production–distribution problem in supply chains: modelling and optimisation approach. Fuzzy Information Engineering, 10(2), 260–283.
  27. Tanaka, H., Ichihashi, H., & Asai, K. (1984). A formulation of fuzzy linear programming problem based on comparison of fuzzy numbers. Control and Cybernetics, 13, 185–194.
  28. Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8, 338-353.
  29. Zimmermann, H.J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1, 45-55.

Files

Share

How to cite

Statistics