A selection of level of supplier in supply chain management using binary coded genetic algorithm with a case study towards Pareto optimality
DOI:
https://doi.org/10.31181/jdaic10015072023sKeywords:
Binary coded Genetic Algorithm, Supplier selection, Intuitionistic Fuzzy number, Supply chain management, tournament selection, Pareto optimalityAbstract
In this work, authors discuss the way of selecting level of supplier by using the concept of binary coded genetic algorithm. For the best solution due to involvement of multi objective functions, the process of Tournament selection is widely discussed. In addition to this, authors involve fuzzy parameters due to the aspiration levels of Decision maker in analysis part for more clarity towards optimality. As a case study towards pareto optimality, the theory of non-dominance of solutions is properly discussed with the help of Pareto frontier. At last the values of objective functions based on quality, cost and service levels following an example are being analyzed with a significant view towards optimality. Based on the optimal solutions, the level of supplier selection is properly discussed.
Downloads
References
Ahmad, I., Liu, Y., Javeed, D., & Ahmad S. (2020). A decision-making technique for solving order allocation problem using a genetic algorithm.IOP Conference Series: Materials Science and Engineering, 853, 012054.
Amid, A., Ghodsypour, S.H., & O’Brien C. (2006). Fuzzy multiobjective linear model for supplier selection in a supply chain. International Journal of Production Economics, 104(2), 394-407.
Aouadni, S., Aouadni, I., & Rebaï, A. (2019). A systematic review on supplier selection and order allocation problems. Journal of Industrial Engineering International, 15, 267-289.
Atanassov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96.
Bellman, R.G., & Zadeh, L.A. (1970). Decision making a fuzzy environment. Management Sciences, 17, B141-B164.
Dulmin, R., & Mininno, V. (2003). Supplier selection using a multi-criteria decision aid method. Journal of Purchasing and Supply Management, 9, 177-187.
Ghobadian, A., Stainer, A., & Kiss, T. (1993). In Proceedings of the First International Symposium on Logistics, 321-328. Nottingham, UK: The University of Nottingham.
Ghodsypour, S.H., & O’Brien C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics, 56-57, 199-212.
Hajikhania, A., Khalilzadeha, M., & Sadjadib S. J. (2018). A fuzzy multi-objective multi-product supplier selection and order-allocation problem in supply chain under coverage and price considerations: An urban agricultural case study. Scientia Iranica, 25(1), 431-449.
Hashim, M., Nazam, M., Yao, L., Baig, S.A., Abrar, M., & Zia-ur-Rehman M. (2017). Application of Multi-Objective Optimization Based on Genetic Algorithm for Sustainable Strategic Supplier Selection under Fuzzy Environment. Journal of Industrial Engineering and Management, 10(2), 188-212.
Khalilzadeh, M., Karami, A., & Hajikhani, A. (2020). The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage. Journal of Modelling in Management, 15(3), 705-725.
Kumar, G.K., Rao, M.S., & Rao, V.V.S.K. (2018). Supplier Selection and Order Allocation in Supply Chain. Materials Today: Proceedings, 5(5), 12161-12173.
Li, M., Fu, Q., Singh, V.P., Ma, M., & Li, X. (2017). An intuitionistic fuzzy multi-objective non-linear programming model for sustainable irrigation water allocation under the combination of dry and wet conditions. Journal of Hydrology 555, 80-94.
Naqvi, M.A., & Amin, S.H. (2021). Supplier selection and order allocation: a literature review. Journal of Data, Information and Management, 3, 125–139.
Singh, S.K., & Yadav, S.P. (2015). Modeling and optimization of multi objective non linear programming problem in intuitionistic fuzzy environment. Applied Mathematical Modelling, 39(16), 4617-4629.
Singh, S.K., & Yadav, S.P. (2016). Fuzzy programming approach for solving Intuitionistic fuzzy linear fractional programming problem. International Journal of Fuzzy Systems, 18(2), 263-269.
Sobhanolahi, M.A., Mahmoodzadeh, A., & Naderi, B. (2018). A max-min fuzzy approach for supplier selection and order allocation problem with transportation costs. Journal of Industrial and Systems Engineering, 11(4), 204-215.
Trisna, T., Marimin, M., Arkeman, Y., & Sunarti, T.C. (2016). Multi-objective optimization for supply chain management problem: A literature review. Decision Science Letters, 5,283-316.
Tsai, W., & Wang, C. (2010). Decision making of sourcing and order allocation with price discounts. Journal of Manufacturing Systems, 29 (1), 47-54.
Wang, T.Y., & Yang, Y.H. (2009). A fuzzy model for supplier selection in quantity discount environments. Expert Systems with Applications, 36 (10), 12179-12187.
Weber, C. A., Current, J.R., & Benton W.C. (1991). Vendor selection criteria and methods. European Journal of Operational Research, 50 (1), 2-18.
Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1, 45-55.
All site content, except where otherwise noted, is licensed under the 