Designing optimal transport networks

  title={Designing optimal transport networks},
  author={G Li and Saulo D. S. Reis and Andr{\'e} A. Moreira and Shlomo Havlin and H. Eugene Stanley and Jos{\'e} S. Andrade},
We investigate the optimal design of networks for a general transport system. Our network is built from a regular two-dimensional (d = 2) square lattice to be improved by adding long-range connections (shortcuts) with probability Pij ∼ r −α ij , where rij is the Euclidean distance between sites i and j, and α is a variable exponent. We introduce a cost constraint on the total length of the additional links and find optimal transport in the system for α = d + 1. Remarkably, this condition… Expand

Figures from this paper

Scaling relations and finite-size scaling in gravitationally correlated lattice percolation models
Abstract In some systems, the connecting probability (and thus the percolation process) between two sites depends on the geometric distance between them. To understand such process, we proposeExpand
Emergence of scaling in ecological communities from tropical forests to human mobility
This work is mainly focused on the study of the interrelationships between transportation networks and the structure of the ecological communities in which the transport takes place. TransportationExpand
Morphological organization of point-to-point transport in complex networks
This work investigates the structural organization of the point-to-point electric, diffusive or hydraulic transport in complex scale-free networks and finds a global “tree-cluster-tree” structure that is universal and leads to a power law decay of the currents distribution. Expand
Comparing two classes of biological distribution systems using network analysis
This study uses network-based methods to identify both common features and variations in the network structure of different classes of biological transport systems, and finds that although both the vasculature and mycelia are highly constrained planar networks, there are clear distinctions in how they balance tradeoffs in network measures of wiring length, efficiency, and robustness. Expand
Crossover from mean-field to 2d Directed Percolation in the contact process
Abstract We study the contact process on spatially embedded networks, consisting of a regular square lattice with long-range connections. To generate the networks, we start from a square lattice and,Expand
Application of Complex Networks Theory in Urban Traffic Network Researches
Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urbanExpand
Framework based on communicability to measure the similarity of nodes in complex networks
A method to measure nodes’ similarity based on network communicability that can more accurately quantify the similarity between nodes from a global perspective is presented. Expand
Data, Methods, and Applications of Traffic Source Prediction
A comprehensive review of the data, methods, and applications of traffic source prediction, which has triggered a number of applications ranging from travel demand control to vehicle routing guidance and infrastructure upgrades. Expand
Network extraction by routing optimization
This work introduces a method to extract network topologies from dynamical equations related to routing optimization under various parameters’ settings and proposes a principled model to address the filtering in the last step, and gives a quantitative interpretation in terms of a transport-related cost function. Expand
Nonlocal PageRank
This work introduces and study a nonlocal version of the PageRank that explores the graph using longer excursions than just moving between neighboring nodes, and shows that the predictive value of the rankings obtained is considerably improved on different real world problems. Expand


Nature (London) 406
  • 845 (2000); Proc. 32nd ACM Symposium on Theory of Computing 163–170
  • 2000
  • Rev. Lett. 102, 058701
  • 2009
How relevant are features for network structure
Physica A 314
  • 109
  • 2002
and M
  • A. de Menezes, Phys. Rev. E 65, 056709
  • 2002
Nature (London) 400
  • 107
  • 1999
Nature (London) 401
  • 130
  • 1999
  • Rev. Lett. 82, 3180, 5180
  • 1999
Nature 393
  • 440
  • 1998