In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.
1 September 2008 in Computers & Industrial Engineering
In this paper, we investigated a third-party logistics (3PL) provider evaluation problem considering social sustainability as one of the important evaluation criteria. Since the 3PL service is mainly dependent on both transport vehicles and employees, managing them from the viewpoint of social sustainability has become a critical issue. Thus, 3PL providers need to be concerned about not only the service price or quality but also issues related to social sustainability. In line with this trend, we defined the social sustainability of 3PL providers and related evaluation criteria. In addition, a fuzzy analytic hierarchy process (AHP) was used as a main evaluation framework to help decision-makers determine the relative importance of each criteria or alternative using linguistic terms. To show the feasibility of the proposed criteria and evaluation framework, we presented the illustrative example based on a real-world case. The results showed that the proposed approach could be a good alternative to conduct evaluations, and the related sensitivity analysis, considering social sustainability.