Comparison of exact and approximate approaches to UAVs mission contingency planning in dynamic environments
Author:
Affiliation:
1. Faculty of Electronics and Computer Science, Koszalin University of Technology, Poland
2. Department of Information Systems, Kielce University of Technology, Kielce, Poland
3. Department of Materials and Production, Aalborg University, Denmark
Abstract
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine
Reference43 articles.
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3. Y. Khosiawan, A. Khalfay, I. Nielsen, Scheduling unmanned aerial vehicle and automated guided vehicle operations in an indoor manufacturing environment using differential evolution-fused particle swarm optimization, Int. J. Adv. Rob. Syst., 15 (2018). https://doi.org/10.1177/1729881417754145
4. S. M. Patella, G. Grazieschi, V. Gatta, E. Marcucci, S. Carrese, The adoption of green vehicles in last mile logistics: a systematic review, Sustainability, 13 (2021), 6. https://doi.org/10.3390/su13010006
5. I. Sung, P. Nielsen, Zoning a service area of unmanned aerial vehicles for package delivery services, J. Intell. Rob. Syst., 97 (2020), 719–731. https://doi.org/10.1007/s10846-019-01045-7
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