## 5 Conclusions and Recommendation  
In this study, the driving force for UAV technology application in the logistics industry is summarized into three points: the rapidly increasing delivery demand, increasing labor costs, and complicated service scenarios. Delivery companies have started facing high labor costs and difficult terminal delivery; how to deliver requests to customers faster has become the greatest challenge for the provider. UAVs can fulfill the requirements for receiving/delivering services to office buildings, private parks, campuses, and other request-concentrated areas in cities. They can significantly improve delivery performance with their unique flexibility and convenience. Through allocation, diverse types of UAVs will apply the related program algorithms to coordinate the operation, which helps the logistics service provider to achieve as yet unseen high performance, speed, and accuracy. The development of the logistics industry will seamlessly connect suppliers with consumers in the future. It will accomplish the personalized experience of accurate request matching, increasing product value through logistics and rapid product circulation. According to the data provided by Chinese e-commence, applying UAV delivery in remote areas can increase performance by 50-60%, and by adding in rush requests, it can fully use the remaining resources to bring greater revenue for companies. The study applied the penalty factors to the original TSP for promoting customer satisfaction. There are two penalty factors: delay, and early arrival. This offers the maximum profit scheduling and determines whether a rush request can be accepted by combining the unmanned vehicle's limited load weight capacity, and the fact that operating time is inversely proportional to the load weight carried. The rush request will be accepted if the revenue from running the UAV can increase. Otherwise, the rush request will be rejected. This will further optimize the unmanned vehicle's schedule. The study considers the relationship between customer satisfaction, load weight, and operating time. Customer loyalty will increase based on the decision-making process, if customer satisfaction is considered when addressing the shortest distance. The model algorithm established by the study can also be regarded as a useful decision-making tool. The study is the application of TSP in UAV cases. It has included the UAV's limited load weight or capacity, and that its operating time is inversely proportional to the load weight carried. The study designs the environmental condition that does not require all requests to be delivered to the hub or the logistics center, but to be processed directly by the calculation of the schedule for the UAV, considering the maximum profit. Furthermore, it can also improve the traditional VRP, and multiple unmanned vehicles can work together to maximize total profit. In addition, the study only includes one rush request. It can be expanded to contain multiple rush requests in the future, which can retrieve requests in various locations first, then process delivery afterward. After the rush request is accepted, the remaining resources can be more effectively allocated to save more resources for companies, further obtain more profit, complete more requests, and guarantee the market share. The delivery fee standard should include weight and volume. In addition to load weight carried, a UAV also has volume limitations. This study has only discussed the limit of load weight; volume cost and the load volume of a UAV can also be included in the future to create a more realistic scenario and further provide the industry with more references and recommendations. Along with people's constantly improving living standards, the logistics service provider will need to pay more attention to customer satisfaction; therefore, we can also adjust the corresponding weights of penalty factors.