A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands

The closed-loop supply chain network design (CLSCND) has garnered a lot of attention since it can handle economic and environmental issues. Likewise, supply chain coordination (SCC) tools can play an important role in enhancing the performance of the supply chains. This paper proposes a new hybrid method, in which SCC decisions and CLSCND objectives are simultaneously involved. First, this approach makes price, greenness, and advertisement decisions, and then it aims at maximizing profit and minimizing CO2 emission. A new nonlinear programming (NLP) model is developed based on the sensitivity of the return rate to green quality and the customers' maximum tolerance, while the demands are uncertain. In order to overcome the uncertain demands, a robust optimization (RO) model is used. A Lagrangian relaxation algorithm is also employed to solve large-scale instances in a logical running time. The applicability of the proposed approach is corroborated through several examples. The results indicate an improvement in the performance of economic and environmental objectives under greening and advertising decisions. Furthermore, the proposed RO model outperforms the model that does not consider a robust approach.

Automated summary

The paper proposes a new hybrid method that simultaneously involves SCC decisions and CLSCND objectives, aiming to maximize profit and minimize CO2 emission through price, greenness, and advertisement decisions. The applicability of the approach is validated through several examples, showing an improvement in economic and environmental objectives under greening and advertising decisions.