A flexible reference point-based multi-objective evolutionary algorithm: An application to the UAV route planning problem

Köksalan, Mustafa Murat
We study the multi-objective route planning problem of an unmanned air vehicle (UAV) moving in a continuous terrain. In this problem, the UAV starts from a base, visits all targets and returns to the base in a continuous terrain that is monitored by radars. We consider two objectives: minimizing total distance and minimizing radar detection threat. This problem has infinitely many Pareto-optimal points and generating all those points is not possible. We develop a general preference-based multi-objective evolutionary algorithm to converge to preferred solutions. Preferences of a decision maker (DM) are elicited through reference point(s) and the algorithm converges to regions of the Pareto-optimal frontier close to the reference points. The algorithm allows the DM to change his/her reference point(s) whenever he/she so wishes. We devise mechanisms to prevent the algorithm from producing dominated points at the final population. We also develop mechanisms specific to the UAV route planning problem and test the algorithm on several UAV routing problems as well as other well-known problem instances. We demonstrate that our algorithm converges to preferred regions on the Pareto-optimal frontier and adapts to changes in the reference points quickly.


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Tezcaner, Diclehan; Köksalan, Mustafa Murat (Springer Science and Business Media LLC, 2011-08-01)
We address the route selection problem for Unmanned Air Vehicles (UAV) under multiple objectives. We consider a general case for this problem, where the UAV has to visit several targets and return to the base. We model this problem as a combination of two combinatorial problems. First, the path to be followed between each pair of targets should be determined. We model this as a multi-objective shortest path problem. Additionally, we need to determine the order of the targets to be visited. We model this as ...
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Türeci, Hannan; Köksalan, Murat; Tezcaner Öztürk, Diclehan; Department of Industrial Engineering (2017)
We study the route planning problem of unmanned air vehicles (UAVs). We consider two objectives; minimizing total distance traveled and minimizing total radar detection threat since these objectives cover most of the other related factors. We consider routing in a two-dimensional continuous terrain, in which we have infinitely many efficient trajectories between target pairs. We develop interactive algorithms that find the most preferred solution of a route planner (RP), who has either of the underlying pre...
A simulation study of ad hoc networking of UAVs with opportunistic resource utilization networks
Lilien, Leszek T.; BEN OTHMANE, Lotfi; Angın, Pelin; DECARLO, Andrew; Salih, Raed M.; BHARGAVA, Bharat (Elsevier BV, 2014-02-01)
Specialized ad hoc networks of unmanned aerial vehicles (UAVs) have been playing increasingly important roles in applications for homeland defense and security. Common resource virtualization techniques are mainly designed for stable networks; they fall short in providing optimal performance in more dynamic networks such as mobile ad hoc networks (MANETs)-due to their highly dynamic and unstable nature. We propose application of Opportunistic Resource Utilization Networks (Oppnets), a novel type of MANETs, ...
Autonomous quadrotor flight with vision-based obstacle avoidance in virtual environment
Eresen, Aydin; Imamoglu, Nevrez; Efe, Mehmet Onder (Elsevier BV, 2012-01-01)
In this paper, vision-based autonomous flight with a quadrotor type unmanned aerial vehicle (UAV) is presented. Automatic detection of obstacles and junctions are achieved by the use of optical flow velocities. Variation in the optical flow is used to determine the reference yaw angle. Path to be followed is generated autonomously and the path following process is achieved via a PID controller operating as the low level control scheme. Proposed method is tested in the Google Earth (R) virtual environment fo...
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Semiz, Fatih; Polat, Faruk (Elsevier BV, 2020-4)
In real life, providing security for a set of large areas by covering the area with Unmanned Aerial Vehicles (UAVs) is a difficult problem that consist of multiple objectives. These difficulties are even greater if the area coverage must continue throughout a specific time window. We address this by considering a Vehicle Routing Problem with Time Windows (VRPTW) variation in which capacity of agents is one and each customer (target area) must be supplied with more than one vehicles simultaneously without v...
Citation Formats
E. DAŞDEMİR, M. M. Köksalan, and D. TEZCANER ÖZTÜRK, “A flexible reference point-based multi-objective evolutionary algorithm: An application to the UAV route planning problem,” COMPUTERS & OPERATIONS RESEARCH, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51797.