A Fuzzy Two-Echelon Model to Optimize Energy Consumption in an Urban Logistics Network with Electric Vehicles

With the increase in pollutants, need to use electric vehicles (EVs) various urban logistics activities is an increasingly important issue. Currently, there are issues with efficiency of transport companies recognizing effects uncertain factors daily operations. Thus, this research proposes a novel fuzzy two-echelon vehicle routing problem involving heterogeneous fleet EVs and internal combustion (ICVs). The first echelon recyclable wastes collected from waste pickup points transported primary centers by EVs. second transporting recycling ICVs. In proposed models, numbers used express rate energy consumption depending on amount load, speed, waste. addition, penalty cost time windows considered both echelons. models solved CPLEX two meta-heuristic algorithms, gray wolf optimizer (GWO) tabu search (TS), based different instance sizes. results show algorithms.