Incorporating CO2 emission trading in the optimal design and planning of chemical supply chain networks under uncertainty

In this work, we analyze the effect of incorporating the CO2 emission trading on the optimal design of chemical supply chain (SC) networks considering simultaneously their economic and environmental performance. We present multi-scenario mixed-integer stochastic linear programming (MILP) model with the unique feature of accounting for the effects of CO2 emissions right cost uncertainty on the economical performance of the network. The uncertain parameter is modeled by a set of scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are explicitly incorporated in the model formulation through standard algebraic equations. The capabilities of the approach presented are illustrated through a case study.