An Ant Colony Heuristic for the Design of Two-Edge Connected Flow Networks

  • Efstratios Rappos
  • Eleni Hadjiconstantinou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3172)


We consider the problem of designing a reliable network defined as follows: Given an undirected graph, the objective of the problem is to find a minimum cost network configuration such that the flow balance equations are satisfied and the network is two-edge connected. The cost function for each edge consists of a fixed component and a variable component, which is proportional to the flow passing through the edge. We present a novel ant colony approach for the solution of the above problem. Computational experience is reported.


Travelling Salesman Problem Network Design Problem Quadratic Assignment Problem Minimum Cost Network Hard Optimization Problem 
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  1. Bonabeau, E., Dorigo, M., Theraulaz, G.: Inspiration for optimization from social insect behavior. Nature 406, 39–42 (2000)CrossRefGoogle Scholar
  2. Colorni, A., Dorigo, M., Maffioli, F., Maniezzo, V., Righini, G., Trubian, M.: Heuristics from nature for hard combinatorial optimization problems. International Transactions in Operational Research 3(1), 1–21 (1996)zbMATHCrossRefGoogle Scholar
  3. Costa, D., Hertz, A.: Ants can colour graphs. Journal of the Operational Research Sociaty 48, 295–305 (1997)zbMATHGoogle Scholar
  4. Dorigo, M., Gambardella, L.M.: Ant colonies for the traveling salesman problem. Technical Report TR/IRIDIA/1996-3, Université Libre de Bruxelles (1996)Google Scholar
  5. Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics (Part B) 26(1), 29–41 (1996)CrossRefGoogle Scholar
  6. Dorigo, M., Stützle, T.: The ant colony optimization metaheuristic: algorithms, applications, and advances. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics, vol. ch. 9, pp. 251–285. Kluwer Academic, Dordrecht (2003)Google Scholar
  7. Gambardella, L.M., Taillard, É., Agazzi, G.: MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In: Corne, D., Dorigo, M., Glover, F. (eds.) New ideas in optimization, pp. 63–76. McGraw-Hill, London (1999)Google Scholar
  8. Gomez, J., Khodr, H., De Oliveira, P., Ocque, L., Yusta, J., Villasana, R., Urdaneta, A.: Ant colony system algorithm for the planning of primary distribution circuits. IEEE Transactions on Power Systems 19(2), 996–1004 (2004)CrossRefGoogle Scholar
  9. Hochbaum, D.S., Segev, A.: Analysis of a flow problem with fixed charges. Networks 19, 291–312 (1989)zbMATHCrossRefMathSciNetGoogle Scholar
  10. Talbi, E.-G., Roux, O., Fonlupt, C., Robillard, D.: Parallel and colonies for the quadratic assignment problem. Future Generation Computer Systems 17(4), 441–449 (2001)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Efstratios Rappos
    • 1
  • Eleni Hadjiconstantinou
    • 2
  1. 1.Information and Analysis Directorate (Operational Research), Department for Work and PensionsThe AdelphiLondonUnited Kingdom
  2. 2.Tanaka Business SchoolImperial College LondonLondonUnited Kingdom

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