An analysis on sustainable one-to-one pickup and delivery problem with heterogeneous vehicles

Effective planning of the logistics management process is considered as one of the ways for businesses to achieve comparative advantage among their competitors. In order to achieve sustainable growth, which has become increasingly important in recent years, practices aiming to prevent environmental pollution and reducing environmental damage have started to be preferred within the framework of sustainable logistics management. For this purpose, it is observed that electric motor vehicles using alternative energy sources are used in the distribution plans. This thesis addresses one to one pickup and delivery problem, which is a type of vehicle routing problem. Unlike the studies on the problem of one to one pickup and delivery in the literature, in this thesis, it is assumed that the vehicle fleet to be used for distribution consists of diesel and electric vehicles, and evaluations are made on fuel consumption and emission indicators on different scenarios using the Mixed Integer Programming model. It is thought that this aspect of the study will contribute to sustainable logistics management literature. As a result of numerical analysis, the benefits of using electric motor vehicles in short-haul freight transportation are revealed in terms of both cost and emissions from transportation operations. Additionally, a cost analysis was carried out on a potential investment, which aims to build solar panels to produce the electric energy that is required by electric vehicles. Since this investment in solar panels has a low rate of return (average 6%), it is concluded that the investment in question is not financially viable. On the other hand, considering the environmental benefit to be obtained, the investment is thought to contribute to sustainability in freight transportation. Key words: Sustainable logistics, short-haul freight transportation, One-to-One Pickup and Delivery Problem, Heterogeneous vehicles, Energy consumption, CO2 Emissions