Mathematical programming model for the optimal management of carbon intensity indicators in global supply chains

Abstract

We propose a rigorous approach for the operational planning of supply chains considering carbon intensity limits in final products. Accurately tracking of these indicators along the value chain can be challenging when dealing with bulk products. Production, transportation, blending and separation of components yield a complex pooling problem within a network structure. A novel mixed-integer nonlinear model is developed to optimize shipping schedules, inventories, processing and distribution of products while complying with environmental constraints of different markets. The model allows for rigorous monitoring and managing of carbon indicators, as well as for drawing important conclusions about sourcing strategies. A decomposition algorithm is presented for this problem, which permits obtaining high quality solutions in reasonable times. A global scale case study is solved to illustrate the economic impact of operating under carbon intensity limits, as well as suggesting alternative operating modes when the penalties on exceeding carbon targets are high.