# Multi-Location Assortment Optimization with Drone and Human Courier Joint Delivery
## 2 Literature Review  
Drone-related research has boomed in recent years, with some researchers paying attention to the customer acceptance of drones. [PERSON] et al. researched public perception and acceptance of drones, focusing on their safety and stability. They found privacy, military use, and abuse were the public's top concerns [6]. [PERSON] et al. used an extended technology acceptance model to assess the customer adoption of drone technology for food-delivery services and determined the factors that influence customer choice of drone delivery [7]. [PERSON] explored public attitudes towards more than 40 applications of drones by quantitative survey study. Except for public security and scientific research applications, the acceptance of drones is not high at present, especially for commercial and hobby use, where it is considered to be a dangerous technology that directly interferes with privacy [8]. Some researchers have focused on the environmental influence of using drones. [PERSON] et al. studied the impact of drone and motorcycle delivery on the environment [9]. They compared the expected environmental improvement of drone delivery in urban and rural areas and found the particulates generated by drone delivery to be half that of motorcycle delivery. [PERSON] et al. studied truck-drone co-delivery and evaluated a last-mile delivery solution for drone-equipped electric trucks, including environmental and economic sustainability [10]. The solution was compared with traditional logistics systems, and results showed that the truck-drone alternative could significantly reduce emissions. Another important stream of research is the design of drone distribution networks. Some researchers focus on finding the optimal drone base station. [PERSON] et al. considered a maximum coverage capacitated facility location problem [11]. They presented an integer linear programming formulation to maximize coverage while explicitly incorporating drone energy consumption and range constraints. [PERSON] et al. considered the 3D location problem of multiple drone base stations (DBSs) together with the allocation of the resources to serve users in a wireless communication network [12]. The problem was formulated as a dynamic capacitated single-source location-allocation problem. [PERSON] et al. presented a modeling framework using EU-wide high-resolution population and land-use data [13]. This framework could estimate the potential optimal location of drone beehives based on economic viability criterion. Some researchers study the routing problem for drones or drones and trucks. [PERSON] and [PERSON] dealt with the problem of delivering orders to a set of customer locations using multiple drones that operate in conjunction with a single truck [14]. [PERSON] and [PERSON] studied the k-Multi-visit Drone-Routing Problem (k-MVDRP) [15]. In this paper, drones could carry multiple heterogeneous packages, and they allowed the specification of a drone energy-drain function that took into account each package's weight. [PERSON] and [PERSON] studied the vehicle-routing problem with drones (VRPD), where trucks and drones were both used to deliver parcels to customers [16]. In this problem, drones could travel with a truck, take off from a stop to serve customers, and land at a service hub to travel with another truck, as long as the flying range and loading capacity limitations were satisfied. [PERSON] and [PERSON] proposed a model for destination-link, flow-path, and flow-link problems in UAV networks with applications to sport and media coverage [17]. [PERSON] and [PERSON] considered a mothership and drone-routing problem (MDRP) [18]. The drones had to launch from the mothership, visit some target locations, and then return to the mothership to refuel in this model. [PERSON] etal. addressed the Truck-multi-Drone Team Logistics Problem (TmDTL) [19]. They devoted themselves to visiting a set of points with a truck helped by a team of unmanned aerial vehicles (UAVs) or drones in the minimum time. Furthermore, [PERSON] et al.