Open Access
Issue
E3S Web of Conf.
Volume 469, 2023
The International Conference on Energy and Green Computing (ICEGC’2023)
Article Number 00093
Number of page(s) 11
DOI https://doi.org/10.1051/e3sconf/202346900093
Published online 20 December 2023
  1. A. I. Lobanov Model of cellular automata in Computer Research and Modeling, 2 (3), pp. 273-293, 2010 [CrossRef] [Google Scholar]
  2. J. B. Robinson On the Hamiltonian game (a traveling-salesman problem). Santa Monica, CA: RAND Corporation, 1949. [Google Scholar]
  3. B. Bullnheimer, R. Hartl, and C. Strauss, A new rank based version of the ant system - a computational study, Central European Journal of Operations Research, 7, pp. 25–38, 1999. [Google Scholar]
  4. I. Slavkov, D. Carrillo-Zapata, N. Carranza, X. Diego, F. Jansson, J.A.Kaandorp, S.Hauert, and J.Sharpe, Morphogenesis in robot swarms, Science Robotics, 3, 2018. doi:10.1126/scirobotics.aau91. [CrossRef] [Google Scholar]
  5. V. Nagalingam and S. Kumar., Development of collision free path planning algorithm for warehouse mobile robot, Procedia Computer Science, 133, pp. 456–463, 2018. doi:10.1016/j.procs.2018.07.056. [Google Scholar]
  6. S. Benhlima, L. Chaymaa, and A. Bekri, Genetic algorithm based approach for autonomous mobile robot path planning, Procedia Computer Science, 127(03), 2018. doi:10.1016/j.procs.2018.01.113. [Google Scholar]
  7. S. Carabaza, A. Galvez, and A. Iglesias, Rank-based ant system with originality reinforcement and pheromone smoothing, Applied Sciences, 12, p. 11219, 2022. doi:10.3390/app122111219. [CrossRef] [Google Scholar]
  8. S. K. Christopher Leet, Jiaoyang Li, Scalable, robust and persistent multi-agent path finding with performance guarantees, in Proceedings of the AAAI Conference on Artificial Intelligence, 36(9), pp. 9386–9395, 2022. [CrossRef] [Google Scholar]
  9. J. Li, A. Tinka, S. Kiesel, J. W. Durham, T. K. S. Kumar, and S. Koenig, Lifelong multiagent path finding in large-scale warehouses, in Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), pp. 11272–11281, 2021. [CrossRef] [Google Scholar]
  10. E. W. Dijkstra, A note on two problems in connexion with graphs, Numer. Math., 1, p.269–271, 1959. [CrossRef] [Google Scholar]
  11. D. Delling, P. Sanders, D. Schultes, and D. Wagner, Engineering route planning algorithms, in Algorithmics of large and complex networks, pp. 117–139, Springer, 2009. [CrossRef] [Google Scholar]
  12. R. Stern, Multi-agent path finding–an overview, Artificial Intelligence, pp. 96–115, 2019. [Google Scholar]
  13. J. Yu, Intractability of optimal multirobot path planning on planar graphs, IEEE Robotics and Automation Letters, 1(1), pp. 33–40, 2015. [Google Scholar]
  14. M.Cap, P.Novak, A.Kleiner, M.Selecky, Prioritized planning algorithms for trajectory coordination of multiple mobile robots, IEEE transactions on automation science and engineering, 12 (3), pp. 835–849, 2015. [Google Scholar]
  15. D. Silver, Cooperative pathfinding, in Proceedings of the First Artificial Intelligence and Interactive Digital Entertainment Conference, June 1-5, 2005, Marina del Rey, California, USA (R. M. Young and J. E. Laird, eds.), pp. 117–122, AAAI Press, 2005. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.