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Local cost minimization in ant transport networks: from small-scale data to large-scale trade-offs
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
Fordham Univ, Dept Biol Sci, Bronx, NY 10458 USA..
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics.
Univ Sydney, Sch Biol Sci, Sydney, NSW 2006, Australia..
2015 (English)In: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 12, no 112, 20150780Article in journal (Refereed) Published
Abstract [en]

Transport networks distribute resources and information in many human and biological systems. Their construction requires optimization and balance of conflicting criteria such as robustness against disruptions, transport efficiency and building cost. The colonies of the polydomous Australian meat ant Iridomyrmex purpureus are a striking example of such a decentralized network, consisting of trails that connect spatially separated nests. Here we study the rules that underlie network construction in these ants. We find that a simple model of network growth, which we call the minimum linking model (MLM), is sufficient to explain the growth of real ant colonies. For larger networks, the MLM shows a qualitative similarity with a Euclidean minimum spanning tree, prioritizing cost and efficiency over robustness. We introduce a variant of our model to show that a balance between cost, efficiency and robustness can be also reproduced at larger scales than ant colonies. Remarkably, such a balance is influenced by a parameter reflecting the specific features of the modelled transport system. The extended MLM could thus be a suitable source of inspiration for the construction of cheap and efficient transport networks with non-zero robustness, suggesting possible applications in the design of human-made networks.

Place, publisher, year, edition, pages
2015. Vol. 12, no 112, 20150780
Keyword [en]
transport networks, network growth model, graph theory, ant collective behaviour, ant colony, network optimization
National Category
Other Natural Sciences Mathematics Other Biological Topics
Identifiers
URN: urn:nbn:se:uu:diva-268402DOI: 10.1098/rsif.2015.0780ISI: 000363987900009OAI: oai:DiVA.org:uu-268402DiVA: diva2:878498
Available from: 2015-12-09 Created: 2015-12-04 Last updated: 2017-12-01Bibliographically approved
In thesis
1. Modelling collective movement and transport network formation in living systems
Open this publication in new window or tab >>Modelling collective movement and transport network formation in living systems
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The emergence of collective patterns from repeated local interactions between individuals is a common feature to most living systems, spanning a variety of scales from cells to animals and humans. Subjects of this thesis are two aspects of emergent complexity in living systems: collective movement and transport network formation. For collective movement, this thesis studies the role of movement-mediated information transfer in fish decision-making. The second project on collective movement takes inspiration from granular media and soft mode analysis and develops a new approach to describe the emergence of collective phenomena from physical interactions in extremely dense crowds. As regards transport networks, this thesis proposes a model of network growth to extract simple, biologically plausible rules that reproduce topological properties of empirical ant trail networks.  In the second project on transport networks, this thesis starts from the simple rule of “connecting each new node to the closest one”, that describes ants building behavior, to study how balancing local building costs and global maintenance costs influences the growth and topological properties of transport networks. These projects are addressed through a modeling approach and with the aim of identifying minimal sets of basic mechanisms that are most likely responsible of large-scale complex patterns. Mathematical models are always based on empirical observations and are, when possible, compared to experimental data.

Place, publisher, year, edition, pages
Uppsala: Department of Mathematics, 2016. 56 p.
Series
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 96
Keyword
animal collective behaviour, transport networks, crowd dynamics, complex systems, ants, fish
National Category
Mathematics
Research subject
Applied Mathematics and Statistics
Identifiers
urn:nbn:se:uu:diva-303943 (URN)978-91-506-2599-8 (ISBN)
Public defence
2016-11-25, Häggsalen, Ångströmslaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2016-11-03 Created: 2016-09-27 Last updated: 2016-11-15

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Bottinelli, AriannaSumpter, David J. T.

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