# A Two-Echelon Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations
## 2 Literature Review
### Related Research on the EVRP  
Considering the threat of generated pollution in the transportation system, research on the Green Vehicle Routing Problem (GVRP) has become a hot issue [9]. As an extension of the GVRP, the EVRP has been studied for many years, such as by [PERSON] et al. [10] and [PERSON] et al. [11]. In the past ten years, with the popularity of EVs around the world, there has been a myriad of research carried out on the use of EVs in the field of the transportation system [12].  
The first to consider optimization algorithms for EVs were [PERSON] and [PERSON] [13]. In their paper, the batteries of EVs can be recharged at customer locations with extra recharging costs. The research regarding the technical and market background of EV demand distribution, as well as a review of EVRP's research work were presented by [PERSON] et al. [14]. The main studies on EVs in the field of transportation research were summarized in their work. Many advantages provided by EVs were given by them, such as frequent stop-and-go, low driving speed, and reduction in air pollution. Time window constraints for customer delivery and restrictions on recharging stations (RSs) were studied by [PERSON] et al. [15]. Four variants of the EVRP considering time windows categorized by the allowable charging times of each route and the battery charging scheme (full recharge or partial recharge) were studied by [PERSON] et al. [16]. The BSS location routing problem with capacitated EVs, which aims to determine the locations of BSSs and their routing plan, was proposed by [PERSON] and [PERSON] [17]. An online routing problem regarding EVs was presented by [PERSON] and [PERSON] [18]. Their aim was to make an occasional detour for vehicles by booking a battery to benefit future vehicles, thereby minimizing the average delay of all vehicles. For a given EV transportation network, how to achieve the solution with the shortest transportation time was stated in [PERSON] et al. [19]. From an environmental perspective, [PERSON] et al. [20] studied EVRP considering RSs to find the minimized energy consumption routing plan. [PERSON] [21] considered the nonlinear recharging times at stations and optimized the EVRPTW with multiple depots. [PERSON] et al. [22] researched the Electric Vehicle Routing Problem with Time Windows and Synchronized Mobile Battery Swapping (EVRPTW-SMBS), which considered Battery Swapping Vans to recharge EVs in a designated time and space.  
A branch-price-and-cut algorithm proposed by [PERSON] et al. [16] aimed to optimally solve four variants of the problem in their work. They also found the optimal solution for instances with up to 100 customers and 21 RSs. However, the EVRP was more commonly solved by heuristics. The electric vehicle routing problem considering time windows and recharging stations (E-VRPTW) was stated by [PERSON] et al. [15] and the hybrid heuristic combining VNS and Tabu search was considered to solve the E-VRPTW. To solve the BSS location routing problem involving capacitated vehicles, methods on how to extend algorithms to the vehicle routing problems considering intermediate stops were shown in [PERSON] et al. [23]. Their work improved the best solutions previously found for the instances of [PERSON] and [PERSON] [17] by using the proposed extended adaptive variable neighborhood search (AVNS) algorithm. An adaptive large neighborhood search (ALNS) algorithm was introduced by [PERSON] and [PERSON] [24] for the EVRP considering partial recharging. [PERSON] et al. [25] applied EVs in the second echelon of the two-echelon transportation system, which was named as the electric two-echelon vehicle routing problem (E2 EVRP).