Inventory Routing Problem with Priorities and Greenhouse Gas Emissions Reduction

In this research, the Inventory Routing Problem (IRP) with priority customers under a green measure to reduce emissions is studied. In general, the IRP involves deciding which clients to visit, how much product to deliver, and the order of visits. The IRP presented here is inspired by a real-world problem faced by a company that produces and distributes gases. In this case, we focus on the distribution of oxygen. A mixed-integer linear programming model is presented to minimize greenhouse gas emissions and include priority for clients in the health sector. The need to incorporate priority for this set of clients is to fulfill the requirements of Mexican law to maintain product quality. The model utilizes a Comprehensive Modal Emission Model (CMEM) formulation to calculate the fuel consumption of heavy-duty vehicles and then, through a factor, obtain the emissions per liter of diesel consumed. The model was implemented using CPLEX, and a set of adapted benchmark instances were solved. The main results show that the minimal average emissions are obtained with instances having 0% priority. When customers are prioritized, the routes are restructured, leading to increased emissions generated. The extent of the increase will depend on the location of the prioritized customers.