1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Braess' Paradox for Pendant Twins

      Preprint

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The Kemeny's constant \(\kappa(G)\) of a connected undirected graph \(G\) can be interpreted as the expected transit time between two randomly chosen vertices for the Markov chain associated with \(G\). In certain cases, inserting a new edge into \(G\) has the counter-intuitive effect of increasing the value of \(\kappa(G)\). In the current work we identify a large class of graphs exhibiting this "paradoxical" behavior - namely, those graphs having a pair of twin pendant vertices. We also investigate the occurrence of this phenomenon in random graphs, showing that almost all connected planar graphs are paradoxical. To establish these results, we make use of a connection between the Kemeny's constant and the resistance distance of graphs.

          Related collections

          Most cited references7

          • Record: found
          • Abstract: not found
          • Article: not found

          Random planar graphs

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            A Markovian model of evolving world input-output network

            The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Kemeny’s constant and an analogue Of Braess’ paradox for trees

                Bookmark

                Author and article information

                Journal
                27 September 2019
                Article
                1909.12549
                e1df94ab-9f18-443a-aef0-32dee0c09fa9

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                05C81, 05C50, 60J10, 05C12, 05C80, 94C15
                14 pages, 2 figures
                math.CO math.PR

                Combinatorics,Probability
                Combinatorics, Probability

                Comments

                Comment on this article