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.
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