A hybrid modeling approach for green and sustainable closed-loop supply chain considering price, advertisement and uncertain demands. (July 2021) - Khorshidvand, Behrooz; Soleimani, Hamed; Sibdari, Soheil; Mehdi Seyyed Esfahani, Mir
Graphical abstract: Highlights: A new hybrid modeling for a green and sustainable closed-loop supply chain is developed. Supply chain coordination and supply chain network design are simultaneously considered. A non-linear programming model for pricing, greening, and advertising decisions is extended. Robust scenario-based stochastic programming model to overcome uncertainty is used. A Lagrangian relaxation algorithm for large-scale instances is utilized. Abstract: 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.