*Article* **Facility Location Problem Approach for Distributed Drones**

#### **Jared Lynskey, Kyi Thar, Thant Zin Oo and Choong Seon Hong \***

Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do 17104, Korea; jared@khu.ac.kr (J.L.); kyithar@khu.ac.kr (K.T.); tzoo@khu.ac.kr (T.Z.O.)

**\*** Correspondence: cshong@khu.ac.kr

Received: 2 January 2019; Accepted: 15 January 2019; Published: 20 January 2019

**Abstract:** Currently, industry and academia are undergoing an evolution in developing the next generation of drone applications. Including the development of autonomous drones that can carry out tasks without the assistance of a human operator. In spite of this, there are still problems left unanswered related to the placement of drone take-off, landing and charging areas. Future policies by governments and aviation agencies are inevitably going to restrict the operational area where drones can take-off and land. Hence, there is a need to develop a system to manage landing and take-off areas for drones. Additionally, we proposed this approach due to the lack of justification for the initial location of drones in current research. Therefore, to provide a foundation for future research, we give a justified reason that allows predetermined location of drones with the use of drone ports. Furthermore, we propose an algorithm to optimally place these drone ports to minimize the average distance drones must travel based on a set of potential drone port locations and tasks generated in a given area. Our approach is derived from the Facility Location problem which produces an efficient near optimal solution to place drone ports that reduces the overall drone energy consumption. Secondly, we apply various traveling salesman algorithms to determine the shortest route the drone must travel to visit all the tasks.

**Keywords:** drone deployment; drone port; traveling salesman; facility location problem
