Abstract
In this paper, we study the problem of dynamically routing Unmanned Aerial Vehicles (UAVs) taking into account not only the known requests, their type, pick-up, and delivery locations, and time windows, but also considering traffic, i.e., collision avoidance, and changing weather conditions as well as the arrival of new customer requests or request cancellation by impatient consumers and emergency departures caused by low battery. This problem can be viewed as the dynamic version of the well-known Vehicle Routing Problem with Time Windows (VRRTW), where current routings are subject to change at any time. Its NP-hard character following the vehicle routing and deadlock-avoidance problems implies the need to use a constraint programming based framework that has proven to be effective in various contexts, especially related to the nonlinearity of system characteristics. The approach has been tested on several examples, analyzing customer satisfaction, i.e., service level, throughput (number of serviced requests). Revenue maximization is influenced by different values of the mission parameters, such as the fleet size, travel distance, wind direction, and wind speed. Computational experiments show the results that allow assessing alternative strategies of UAV mission planning.
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References
Backer, B., Furnon, V., Shaw, P., Kilby, P., Prosser, P.: Solving vehicle routing problems using constraint programming and metaheuristics. J. Heuristics 6(4), 501–523 (1999). https://doi.org/10.1023/a:1009621410177
Braekers, K., Ramaekers, K., Van Nieuwenhuyse, I.: The vehicle routing problem: state of the art classification and review. Comput. Ind. Eng. 99, 300–313 (2016). https://doi.org/10.1016/j.cie.2015.12.007
Bullo, F., Frazzoli, E., Pavone, M., Savla, K., Smith, S.L.: Dynamic vehicle routing for robotic systems. Proc. IEEE 99(9), 1482–1504 (2011). https://doi.org/10.1109/jproc.2011.2158181
Grippa, P.: Decision making in a UAV-based delivery system with impatient customers. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5034–5039 (2016). https://doi.org/10.1109/iros.2016.7759739
Holborn, P.L.: Heuristics for dynamic vehicle routing problems with pick-ups and deliveries and time windows. Ph.D. Thesis. School of Mathematics Cardiff University, Cardiff, UK (2013)
Khoufi, I., Laouiti, A., Adjih, C.: A survey of recent extended variants of the traveling salesman and vehicle routing problems for unmanned aerial vehicles. Drones 3(3), 66 (2019). https://doi.org/10.3390/drones3030066
O’Rourke, K.P., Bailey, T.G., Hill, R., Carlton, W.B.: Dynamic routing of unmanned aerial vehicles using reactive Tabu search. In: 67-th MORS Symposium (1999)
Pavone, M., Bisnik, N., Frazzoli, E., Isler, V.: A stochastic and dynamic vehicle routing problem with time windows and customer impatience. Mob. Netw. Appl. 14(3), 350–364 (2008). https://doi.org/10.1007/s11036-008-0101-1
Pillac, V., Gendreau, M., Guéret, C., Medaglia, A.L.: A review of dynamic vehicle routing problems. Eur. J. Oper. Res. 225(1), 1–11 (2012). https://doi.org/10.1016/j.ejor.2012.08.015
Radzki, G., Nielsen, P., Bocewicz, G., Banaszak, Z.: A proactive approach to resistant UAV mission planning. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) AUTOMATION 2020. AISC, vol. 1140, pp. 112–124. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-40971-5_11
Ritzinger, U., Puchinger, J., Hartl, R.F.: A survey on dynamic and stochastic vehicle routing problems. Int. J. Prod. Res. 54(1), 215–231 (2015). https://doi.org/10.1080/00207543.2015.1043403
Thibbotuwawa, A., Bocewicz, G., Nielsen, P., Banaszak, Z.: UAV mission planning subject to weather forecast constraints. In: Herrera-Viedma, E., Vale, Z., Nielsen, P., Martin Del Rey, A., Casado Vara, R. (eds.) DCAI 2019. AISC, vol. 1004, pp. 65–76. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-23946-6_8
Thibbotuwawa, A., Bocewicz, G., Radzki, G., Nielsen, P., Banaszak, Z.: UAV mission planning resistant to weather uncertainty. Sensors 20(2), str. 515 (2020). https://doi.org/10.3390/s20020515
Thibbotuwawa, A., Nielsen, P., Zbigniew, B., Bocewicz, G.: Energy consumption in unmanned aerial vehicles: a review of energy consumption models and their relation to the UAV routing. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds.) ISAT 2018. AISC, vol. 853, pp. 173–184. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99996-8_16
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Radzki, G., Nielsen, P., Thibbotuwawa, A., Bocewicz, G., Banaszak, Z. (2020). Declarative UAVs Fleet Mission Planning: A Dynamic VRP Approach. In: Nguyen, N.T., Hoang, B.H., Huynh, C.P., Hwang, D., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2020. Lecture Notes in Computer Science(), vol 12496. Springer, Cham. https://doi.org/10.1007/978-3-030-63007-2_15
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