Track: Logistics

Abstract

Total supply chain management cost has always been the interest of many companies in these recent economies. The aim to survive and sustain is important these days. Sustainability in road transport operation can be measured by how the transport company manages the fuel consumption for its vehicles or trucks. Fuel efficiency is one of the key points to measure the success of road transport operation. It can be achieved by controlling the right variables such as speed, weight or volume of transported good, travelled distance and other related variables. However, all the variables are highly affected by the logistics uncertainties such road congestion, faulty vehicles, error in information and many more. In this study, a fuel namely diesel usage optimization model that consider the effect of the logistics uncertainties is proposed. The mixed integer programming model that considers truck tonnage, its age, model and travelled distance as the controlled variables while delay, wrong information and changes in demand volume (carried volume) as the constraints is adapted using a 3 month data from a freight forwarding company. The model is solved using Excel Solver and shows that different models at different age are losing the fuel efficient, but the difference is not significant. At the same time, delay and wrong information do not have effect on fuel efficient but changes in demand volume largely affect the fuel efficiency by 20.4 percent for the three-month data. The sensitivity analysis for the upcoming months are also done.