Transportation Cost and CO2 Emissions in Location Decision Models

An increasing number of companies are making their supply chains more sustainable. Because transportation accounts for a large share of global CO2 emissions, finding logistics alternatives that reduce carbon emissions while keeping costs low is a priority. In this article, we study the trade-off between cost and CO2 emissions by using a multiobjective approach for the facility location problem. We propose a model with new cost and CO2 structures for the p-Median problem to determine a sustainable location. To solve this problem, we develop the multiobjective combinatorial optimization cross-entropy method, to address the difficulties of combinatorial models. We test the algorithm against two p-Median problems from prior literature and show that it can approximate the Pareto frontier efficiently. We also conduct an experimental study for a consumer packaged goods company in Mexico City to provide insights on the structure of the Pareto frontier for a practical sustainable facility location case. The study shows that by selectively changing a subset of locations, companies may achieve a substantial reduction in carbon emissions under similar costs