Urban Biology!
Urban Biology!

References - Ant behaviour to solve urban problems

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(8) Youngsteadt, E. et al. (2014). Habitat and species identity, not diversity, predict the extent of refuse consumption by urban arthropods. Global Change Biology, 21(3), 1103-1115.

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(18) Jabbarpour, M. R., Jalooli, A., Shaghaghi, E., Noor, R. M., Rothkrantz, L., Khokhar, R. H., and Anuar, N. B. (2014). Ant-based vehicle congestion avoidance system using vehicular networks. Engineering Applications of Artificial Intelligence, 36, 303-319.

(19) Dorigo, M. and Birattari, M. (2010). Ant Colony Optimization. Encyclopedia of Machine Learning. . Retrieved from http://link.springer.com.proxy.library.uu.nl/referenceworkentry/10.1007%2F978-0-387-30164-8_22#close.

(20) Yang, H. (2014). Study on traveling salesman problem based on the improved chaos ant colony algorithm. Advanced Material Research, 989-994, 2196-2199.

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(22) Rizzoli, A.E., Montemanni, R., Lucibello, E. and Gambardella, L.M. (2007). Ant colony optimization for real-world vehicle routing problems. Swarm intelligence, 1(2), 135-151.

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(24) Karadimas, N. V., Papatzelou, K. and Loumos, V. G. (2007). Optimal solid waste collection routes identified by the ant colony system algorithm. Waste Management and Research, 25(2), 139-147.