Multi-objective programming and Six Sigma approaches for a competitive pharmaceutical supply chain with the value chain and product lifecycle

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 3 sigma is 3.6% more than the profit at the optimization level 6 sigma. The total environmental pollution of the two supply chains at the optimization level 3 sigma is 1.9% less than the environmental pollution at the optimization level 1.285 sigma. The total consumer health level of the two supply chains at the optimization level 3 sigma is 3.3% more than the consumer health level at the optimization level 1.285 sigma. The total brand equity of the two supply chains at the optimization level 3 sigma is 2.5% more than the brand equity at the optimization level 6 sigma. It seems that the optimization level 3 sigma for the two pharmaceutical supply chains is more appropriate than the other optimization levels.

Automated summary

This study examines the design and optimization levels of two pharmaceutical supply chains. Nash equilibrium analysis based on marketing mix factors at different periods of product life is conducted, and a multi-objective mixed-integer nonlinear programming model is proposed to minimize environmental pollution while maximizing profit, consumer health level, and brand equity. The study validates the proposed approach with a real-case study, and suggests that the optimization level of 3 sigma is the most appropriate.