A robust optimization model for sustainable pharmaceutical distribution network design: a case study

Today's communities are struggling with environmental issues such as air pollution and greenhouse effect, and social problems such as creation of jobs, labor welfare, and decent work. In operations and production systems, it is necessary to pay attention to environmental, social and economic issues, which comprise the three dimensions of sustainability. Additionally, rapid change in economy, society and environment contributes to the uncertainty of the situation even. This study considers the concepts of uncertainty and sustainability in a pharmaceutical distribution network. It proposes a new model for sustainable pharmaceutical distribution network under uncertainty with three objectives through a mixed integer linear programming model. The variables of demand and cost of transportation are uncertain. The model was tested in a pharmaceutical distribution company. It was solved with RPP-II approach and using weighted sum, NSGA-II and MOPSO algorithms. After tuning the parameters of algorithms through Taguchi method, the three methods were compared. MOPSO had the best performance to achieve the best Pareto approximate. The output of this novel model helps managers to determine the main and local DCs as strategic decisions and the flow of medicine in each part as operational decisions. These kinds of decisions improve the environmental, social and economic conditions of pharmaceutical distribution networks and it is resistant to price and demand fluctuations in turbulent markets.