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Multi-objective programming and Six Sigma approaches for a competitive pharmaceutical supply chain with the value
Farzaneh Shakouhi1, Reza Tavakkoli-Moghaddam2, Armand Baboli3
1Department of Industrial Engineering, Alborz Campus, University of Tehran, Tehran, Iran.
Abstract:
This study examines two pharmaceutical supply chains (PSCs) under the product life cycle and marketing strategies for the first time. Nash equilibrium between PSCs is based on marketing mix factors (i.e., price, the value provided by the value chain, availability, and promotion) at different periods of product life (i.e., introduction, growth, and maturity). Considering the previous step's outputs, environmental protection, and sustainable development, this study provides a multi-objective mixed-integer nonlinear programming model (MOMINLP) for the design of PSCs to minimize environmental pollution and maximize profit, consumer health level, and brand equity. At this stage of the network design, disruption issues in the manufacturer, distributor, and retailer are considered. Based on the value from the value chain in different periods of product life, different scenarios are considered. Optimizing the supply chain network design (SCND) under uncertainty through the reliability and Six Sigma concepts is examined. The proposed approach is validated with a real-case study in Iran. The results show that the brand equity, pollution created, and supply chain profits decrease with increasing optimization levels. However, the level of consumer health rises with increasing levels of optimization. Based on the obtained results, the total profit of the two supply chains at the optimization level 3σ is 3.6% more than the profit at the optimization level 6σ. The total environmental pollution of the two supply chains at the optimization level 3σ is 1.9% less than the environmental pollution at the optimization level 1.285σ. The total consumer health level of the two supply chains at the optimization level 3σ is 3.3% more than the consumer health level at the optimization level 1.285σ. The total brand equity of the two supply chains at the optimization level 3σ is 2.5% more than the brand equity at the optimization level 6σ. It seems that the optimization level 3σ for the two pharmaceutical supply chains is more appropriate than the other optimization levels.
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