In this paper, an operating cost optimization problem of Electric Vehicles (EVs) is studied in a large-scale logistics and transportation network. An extended EV operational model is proposed for a multiple depots and charge stations environment where practical constraints are included. In the proposed model, new practical mathematical schemes are proposed to describe the constraints. Then, a new Two-step Clustering Heuristic Optimization (TCHO) method is developed to minimize the total operating cost of the EV routes while satisfying all the constraints. In the first step, a novel Heuristic Edge Sharing Assigning Algorithm (HESAA) is designed to split the large scale logistic network into different clusters. In the second step, a new Shortest Path Heuristic (SPH) method is developed to minimize the total expense of the EV routes for each cluster. Furthermore, based on the TCHO, a novel Discrete Differential Evolution-TCHO (DDE-TCHO) is proposed to improve the performance on solving the problem. The effectiveness of the proposed models and methods is verified by comprehensive numerical simulations where the well-known vehicle routing problem benchmarks are applied.