# Multi-Location Assortment Optimization with Drone and Human Courier Joint Delivery
## 1 Introduction  
With the development of the logistics industry, takeout food and online shopping have become an indispensable part of life. Meituan's annual catering takeout transaction volume reached 10.1 billion in 2020, with an annual turnover of CNY 488.9 billion. More than 4.7 million riders earned CNY 48.69 billion from it, accounting for 41% of the total cost and becoming the company's largest expense [1]. However, the complexity of traffic and the instability of delivery time are still urgent problems to be solved. Facing these, new delivery methods and operation modes need to be introduced to improve distribution efficiency and uphold the dogma of zero emissions. Drones have been widely used in various settings for the past few years. Some researchers have explored energy-saving delivery schemes related to drones [2]. The outbreak of COVID-19 has accelerated its development, especially in the transporting of medicine, emergency supplies, and food. In 2022, more than 100,000 orders were delivered between Shanghai and Shenzhen using Meituan's drone delivery business, taking 12 min on average [1]. The demand for drone delivery is increasing. To provide better service, researchers have also recently investigated customer preference for drone delivery. [PERSON] used the discrete choice model (DCM) to characterize consumer preferences for drone delivery compared with truck or motorcycle [3]. It shows that price and commodity type are two big influences on customer preference. Other factors are gender, age, and household income, which reflects that the younger the age, the higher the preference for drone delivery service. [PERSON] et al. designed a goods delivery service by drone based on a preference survey [4]. The result showed that last-mile delivery by drones is appropriate for small andlight packages. As customer acceptance increases, how to optimize the use of drones in transportation will become a novel problem. A drone-based online delivery service now consists of four steps. Initially, a customer browses products listed in different online shops and picks the one she wants. Then, the shop owner prepares the product and takes it to the drone base station. Third, the drone delivers the product to another specified drone base station. Last, the customer receives the product from the specified drone base station. The delivery distance of drones is much shorter than that of ground delivery and is rarely affected by road conditions. Labor costs and time costs are saved using drone delivery, and carbon emissions are reduced as well. For customer services, the delivery time of the drone can also be controlled accurately, which improves delivery stability and customer satisfaction. With the rise in the popularity of drone delivery, online shop owners must expand delivery services to face the challenge of other shops and improve competitiveness. In the retail industry, the product assortment of a store affects the arrival rate of customers, which further affects store revenue. With the development of drone transportation technology and the increased acceptance of drones, it is of great importance to optimize product assortment and distribution methods under drone delivery. Aiming for higher revenue, in this study, we consider a purely online shop network that costs little in terms of storage space and delivers products via cooperative delivery by drones and human couriers. In practice, in some business quarters and industrial parks, takeout delivery and parcel delivery show the characteristics of clustering, which also results in the appearance of locker alliance [5]. Therefore, we assume the start and end of delivery can be considered to be some spots, and the products shown in the online store in this spot are the union of products from offline stores around it. We set a cardinality constraint of the capacity in each online shop, as the customer pays more attention to the products at the top of the list.