A decision support model proposal for sustainable freight transportation

Environmental externalities such as constantly increasing greenhouse gas emissions, depletion of natural resources, global warming, and increasing competition forces companies to take sustainability into account while planning their operations. The need for making efficient and productive freight transportation plans becomes more obvious for firms with the growing transportation activities. Therefore, researchers work on developing decision support models that could be used by decision makers for sustainable freight transportation. In this study, a bi-objective linear programming model is proposed for vehicle allocation problem confronted in the field of sustainable freight transportation. Profit maximization and emission minimization could be done simultaneously for the addressed problem by means of the proposed mathematical model. Therewithal, for the model, consideration of various vehicles among the fleet mix and involving a penalty cost related to demand refusal are regarded as suitable assumptions for cases that could arise in real life, and such features of the model are crucial for decision makers. As far as known; there is no such model available in the literature that considers the aforementioned factors simultaneously. The applicability of the proposed model and the potential benefits that could be obtained from its usage are shown by numerical analyses conducted on a case study. In the numerical analyses, the situations that could be confronted by decision makers in practice are respected. In line with this objective, the revenue and cost information along with the corresponding total profit and total emission quantities are demonstrated in each of the analysis. The study facilitates understanding and applicability of analyses for decision makers by plain presentation, and forms an example in terms of contributing to the understanding of the importance of the sustainability concept in vehicle allocation problems. Numerical analyses on the case study show that total profit observed under profit maximization is ten times higher than the one obtained under emission minimization. Moreover, the total emissions observed under emission minimization is seven times lower than the one obtained under profit maximization. Key Words Sustainable logistics management, road freight transportation, vehicle allocation problems, bi-objective linear programming