Optimizing Two-Echelon Logistics Network for Urban Logistics by LRP Heuristics with integrated Microscopic Transport Simulation

Abstract

In recent years, numerous research efforts and pilot projects have shown that cargo bikes in combination with micro depots (MD) present a sustainable alternative to motor vehicles, particularly in urban logistics. However, a holistic modelling, optimisation and evaluation of freight transport systems requires a close examination of all interactions, both on the strategic as well as on the operational and tactical decision-making level. In this study, we optimize the logistics network of micro depots for a two-stage distribution at urban level from distribution centres via micro depots to the end customers. Additionally, we evaluate the impact of cargo bikes and electric vehicles on the infrastructure layer of a multi-layer network and design a tool for strategic transport and logistics network planning. We introduce this integrated approach to solve the two-echelon location routing problem, i.e. LRP, by using microscopic agent-based transport simulation and divide-and-conquer heuristics. In the framework of a case study focusing on courier, express and parcel (CEP) market for Berlin, Germany, we identify the optimal number and the distribution of the locations for MD to ensure efficient two-stage distribution via MD, utilizing cargo bikes on the very last mile. Finally, we evaluate our results by comparing different scenarios and assessing optimized logistics network by means of microscopic transport simulation. By applying proposed heuristics, we could significantly reduce the number of MD in the delivery area, while also increasing the overall utilization of cargo bicycles.