Low-carbon Two-echelon Supply Network Design With Stochastic Demand

The issue of global climate change has drawn an increasing public attention over the past few decades.Numerous scientific studies have shown its serious negative impact on the environment.Many scientists believe that the dominant cause of global warming is the radioactive forcing driven by anthropogenic greenhouse gas(GHG)emissions.GHGs include carbon dioxide,methane,nitrous oxide,hydrofluorocarbons,perfluorocarbons and sulfur hexafluoride.Among them,carbon dioxide is the major anthropogenic GHG.Many countries have made efforts to reduce carbon emissions by taking measures such as carbon tax,carbon cap-and-trade,carbon cap,and carbon offset.With growing environmental awareness in public,an increasing number of customers are advocating low-carbon lifestyle and green consumption.Under such background,it is not sufficient to design supply chains in a way that only focuses on economic benefits.Nowadays,corporations are more willing to implement carbon reduction strategies to set up a good social image and enhance their competitiveness.This paper proposes a low-carbon two-echelon supply chain network design problem with stochastic demand that incorporates carbon emission considerations.We consider a three-level supply chain that is comprised of an external supplier,a set of distribution center(DC)locations,and a set of retailers.The demand information of a single product,i.e.,the distribution,mean,and variance,is known for each retailer.Each retailer(DC,resp.)replenishes its inventory from a single DC(the supplier)via direct shipment.The model,formulated as a mixed-integer program(MIP),takes into account the total cost,including the fixed location cost,the transportation cost,the fixed ordering cost,the holding cost,the safety stock cost,in addition to the cost of environmental impact measured by carbon emissions coming from the shipment of the products.The problem is to simultaneously optimize the set of DCs to open,the DCretailer assignment,and the DC-retailer echelon inventory replenishment decisions so that the system-wide long-run average fixed location,transportation,fixed ordering,holding,safety stock,and carbon tax costs are minimized.A cutting-plane approach is developed to solve this optimization problem.Meanwhile,we provide some interesting managerial insights based on the computational results.