An integrated supply chain problem with environmental considerations

The continuous rise in environmental awareness has affected several aspects of the global economy, including supply chain management. Traditionally, supply chains are designed and operated in a way that minimizes costs and increases profitability; however, this is not sufficient nowadays. It is of crucial importance to incorporate the target of emissions reduction in the supply chain. Thus, in the current paper we address a joint location-inventory problem and extend it to account for the reduction of carbon emissions. The original problem consists of one plant, multiple distribution centers (DCs) and multiple retailers, with products flowing from a plant to DCs and from there to retailers. We also account for uncertainty by including a new variable that reflects the probability of different demand scenarios. In terms of the solution technique, we develop a Genetic Algorithm (GA) and justify our choice of this heuristic approach by the fact that the resulting model is high in complexity and requires solving within reasonable time. We test the GA with a thorough sensitivity analysis using several chromosome representations, different mutation and crossover probabilities, as well as different evaluation functions. Finally, we validate the accuracy of our GA on small instances that have been solved to optimality using GAMS.