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Identifying main center access hubs in a city using capacity and time criteria. The evolutionary approach

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper we consider the well known Hub and Spoke problem, analyzed in the context of Warsaw Public Transport System. Our method was designed for data preprocessing so as to allow using a timetable obtained from the public transport web site after conversion into the required data format. A dedicated evolutionary algorithm method that detects the hubs of almost all available transport means was also developed. The hubs identified are well connected to the center of the city and to other identified hubs (characterized by high capacity or short travel time). These hubs may become the skeleton of the public transport system and, in particular, good points for locating Park and Ride facilities.
Rocznik
Strony
207--223
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
  • Faculty of Computer Science Warsaw School of Information Technology ul. Newelska 6, 01-447 Warsaw, Poland
  • Systems Research Institute, Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw, Poland
autor
  • Faculty of Computer Science Warsaw School of Information Technology ul. Newelska 6, 01-447 Warsaw, Poland
  • Systems Research Institute, Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw, Poland
autor
  • Systems Research Institute, Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw, Poland
autor
  • Faculty of Computer Science Warsaw School of Information Technology ul. Newelska 6, 01-447 Warsaw, Poland
  • Systems Research Institute, Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw, Poland
Bibliografia
  • [1] Campbell, J.F., O’Kelly, M.E. (2012) Twenty-Five Years of Hub Location Research. Transportation Science, 46 (2), 153–169.
  • [2] Cetiner, S., Sepil, C., Sural, H. (2010) Hubbing and routing in postal delivery systems. Annals of Operations Research, 181, 109–124.
  • [3] Liu, Ch.-Ch. and Chen, Y.-Ch. (2003) The integration of Taiwanese and Chinese air networks for direct air cargo services. Transportation Research Part A: Policy and Practice 37, 7, August 2003, 629–647. Cichosz, P. (2000) Systemy uczące się (Self-learning systems; in Polish). WNT, Warszawa.
  • [4] Cormen, T. H., Leiserson C. E., Rivest R. L., Stein. C. (2009) Introduction to Algorithms. MIT.
  • [5] Coyle, J.J., Bardi E.J, Novack R.A., (1994) Transportation. Fourth Edition, West Publishing Company, New York.
  • [6] Horner M., O’Kelly M.E. (2001) Embedding economy of scale concepts for hub network design. Journal of Transport Geography, 9 (4), 255–265.
  • [7] O’Kelly, M.E, (1987) A quadratic integer program for the location of interacting hub facilities. European Journal of Operational Research 32, 392–404.
  • [8] O’Kelly, M.E., Bryan D. (2002) Interfacility interaction in models of hubs and spoke networks. Journal of Regional Science, 42 (1), 145–165.
  • [9] Mazbic-Kulma, B., Potrzebowski, H., Stańczak, J., Sęp, K. (2008) Evolutionary approach to solve hub-and-spoke problem using α− cliques Evolutionary Computation and Global Optimization, Prace naukowe PW, Warszawa, 121–130.
  • [10] O’Kelly, M.E, (1987) A quadratic integer program for the location of interacting hub facilities. European Journal of Operational Research 32, 392–404.
  • [11] O’Kelly, M.E., Bryan D. (2002) Interfacility interaction in models of hubs and spoke networks. Journal of Regional Science, 42 (1), 145–165.
  • [12] Ma˙zbic-Kulma, B., Potrzebowski, H., Stańczak, J., Sęp, K. (2008) Evolutionary approach to solve hub-and-spoke problem using α− cliques Evolutionary Computation and Global Optimization, Prace naukowe PW, Warszawa, 121–130.
  • [13] Mazbic-Kulma, B., Potrzebowski, H., Sta´nczak, J., Se¸p, K. (2009) Evolutionary approach to find kernel and shell structure of a connection graph Total Logistic Management, AGH, Cracow, 37–50.
  • [14] Min, H., Gou, Z. (2004) The location of hub-seaports in the global supply chain network using a cooperative competition strategy. Integrated Supply Management, 1 (1), 51–63.
  • [15] Michalewicz, Z. (1996) Genetic Algorithms + Data Structures = Evolution Programs. Springer Verlag, Berlin–Heidelberg.
  • [16] Potrzebowski, H., Stańczak, J., Sęp, K. (2006) Evolutionary Algorithm to find graph covering subsets using α - cliques. Evolutionary Computation and Global Optimization, Prace naukowe PW, Warsaw, 351–358.
  • [17] Potrzebowski H., Stańczak J., Sęp K. (2007) Separable decomposition of graph using α-cliques. In: M. Kurzyński, E. Puchal a, M. Woźniak, A. ˙ Zolnierek. eds., Computer recognition systems 2, Advances in soft computing. Springer-Verlag, Berlin-Heidelberg, 386–393.
  • [18] Stańczak, J. (2003) Biologically inspired methods for control of evolutionary algorithms. Control and Cybernetics, 32 (2), 411–433.
  • [19] Stańczak, J., Potrzebowski, H., Se¸p, K. (2011) Evolutionary approach to obtain graph covering by densely connected subgraphs. Control and Cybernetics, 41, 3, 80–107.
  • [20] Sutton, R.S., Barto, A.G. (1998) Reinforcement Learning: An Introduction. MIT Press.
  • [21] Wilson, R.J. (1996) Introduction to graph theory. Addison Wesley Longman.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
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