A hybrid robust possibilistic approach for a sustainable supply chain location-allocation network design

In this paper, a multi-objective multi-period sustainable location-allocation supply chain network model will be presented. Different levels of technology for vehicle fleet, which leads to different monetary and environmental costs, and different released CO2 emission for each potential location of facilities to reach a green supply chain network, were considered. In addition, back order of products, which leads to dissatisfaction of customers, was noted and for different customers, different levels of importance are assumed to consider social impacts. To handle the problem of unpredicted parameters, a novel approach of uncertainty, which is named Hybrid Robust Possibilistic Programming-II (HRPP-II), is used. At last, a case study will be solved by the Improved Augmented ϵ-Constraint method (AUGMECON2) to achieve Pareto solutions, and some sensitivity analysis will be done. New social and environmental considerations in location-allocation supply chain models and using a novel robust approach to overcome the uncertainty of parameters are contributions to the previous models.