Show source-provided references
1. Lu, Y., Liu, Y., Gao, C., Tao, L., and Zhang, Z. (2014, January 17–20). A Novel Physarum-Based Ant Colony System for Solving the Real-World Traveling Salesman Problem. Proceedings of the International Conference in Swarm Intelligence, Hefei, China.
10.1007/978-3-319-11857-4_20 ↗5. Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
7. A solution of TSP based on the ant colony algorithm improved by particle swarm optimization
8. Nechita, E., Crisan, G.C., Lantovics, L.B., and Huang, Y. (2020). On the Resilience of Ant Algorithms. Experiment with Adapted MMAS on TSP. Mathematics, 8.
10.3390/math8050752 ↗10. (2019). Kernighan local search for a real-life Two-Echelon Heterogeneous Vehicle Routing Problem based on Brazilian wholesale companies. Appl. Soft Comput., 76, 697–711.
10.1016/j.asoc.2018.12.036 ↗12. Solving Arc Routing Problems Using the Lin-Kernighan-Helsgaun Algorithm
13. Myxomycetes: A Handbook of Slime Molds by Steven, L. Stephenson
18. Slime mould imitates development of Roman roads in the Balkans
19. Becker, M. (2016, January 24–29). On the quality of graphs generated by swarm algorithms. Proceedings of the IEEE Congress on Evolutionary Computation, Vancouver, BC, Canada.
10.1109/CEC.2016.7744262 ↗20. Meyer-Nieberg, S. (2017, January 15–19). Coordinating a team of searchers: Of ants, swarms, and slime molds. Proceedings of the Genetic & Evolutionary Computation Conference, Berlin, Germany.
10.1145/3071178.3071277 ↗22. Novel Routing Method Using Slime Mold Algorithm Corresponding to Movement of Content Source in Content-Oriented Networks
10.2299/jsp.23.173 ↗31. Liu, Y., Lu, Y., Gao, C., Zhang, Z., and Tao, L. (2014, January 19–21). A multi-objective ant colony optimization algorithm based on the Physarum-inspired mathematical model. Proceedings of the 10th International Conference on Natural Computation, Xiamen, China.
10.1109/ICNC.2014.6975852 ↗32. A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model
10.1088/1748-3182/9/3/036006 ↗33. Zhang, Z., Gao, C., Lu, Y., Liu, Y., and Liang, M. (2016). Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems. PLoS ONE, 11.
10.1371/journal.pone.0146709 ↗35. Route 20, Autobahn 7, and Slime Mold: Approximating the Longest Roads in USA and Germany with Slime Mold on 3-D Terrains
10.1109/TCYB.2013.2248359 ↗36. Uemura, M., Matsushita, H., and Kraetzschmar, G.K. (2015, January 9–12). Path Planning with Slime Molds: A Biology-Inspired Approach. Proceedings of the International Conference on Neural Information Processing, Istanbul, Turkey.
10.1007/978-3-319-26561-2_37 ↗