A new transition rule for ant colony optimization algorithms: Application to pipe network optimization problems

Engineering Optimization

Volumn 37, Issue 5, 2005, Pages 525-540

  Afshar, M H ^a  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

Author keywords

Ant colony system; Optimal design; Pipe networks; Transition rule

Indexed keywords

BENCHMARKING; COMPUTATIONAL METHODS; DECISION MAKING; HEURISTIC METHODS; HYDRAULICS; PROBLEM SOLVING;

ANT COLONY SYSTEM; OPTIMAL DESIGN; PIPE NETWORKS; TRANSITION RULE;

EVOLUTIONARY ALGORITHMS;

EID: 22144461351     PISSN: 0305215X     EISSN: None     Source Type: Journal    
DOI: 10.1080/03052150500100312     Document Type: Article

References (23)

1. Afshar, M.H., An element-by-element algorithm for the analysis of pipe networks. Int. J. Eng. Sci., 2001, 12(3), 87-100.
2. Bullnheimer, B., Hartl, R.F. and Strauss, C., Applying the ant system to the vehicle routing problem. In Mela-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, edited by I.H. Osman, S. Vob, S. Martello and C. Roucairol, 1998 (Kluwer Academic), pp. 109-120.
3. Colorni, A., Dorigo, M and Maniezzo, V., Distributed optimization by ant colonies, In: Proceedings of ECAL91-European Conference on Arificial Life, 1991 (Elsevier Publishing), pp. 134-142.
4. Colorni, A., Dorigo, M., Maniezzo, V. and Trubian, M., Ant system for job-shop scheduling. Belgian J. Operat. Res. Stat. Comput. Sci. (JORBEL), 1994, 34, 39-53.
5. Colorni, A., Dorigo, M., Maffioli, F., Maniezzo, V., Righini, G. and Trubian, M., Heuristics from nature for hard combinatorial optimization problems. Int. Trans. Operat. Res., 1996, 3(1), 1-21.
6. Costa, D. and Hertz, A., Ants can color graphs. J. Oprat. Res. Soc., 1997, 48, 295-305.
7. Dandy, G.C., Simpson, A.R. and Murphy, L.J., An improved genetic algorithm for pipe network optimization. Water Resour. Res., 1996, 32(2), 449-458.
8. Deneubourg, J.-L., Aron, S., Goss, S. and Pasteels, J.-M., The self-organizing exploratory pattern of the argentine ant. J. Insect Behav., 1990, 3, 159-168.
9. Di Caro, G. and Dorigo, M., Extending AntNet for best-effort quality-of-service routing. Unpublished presentation at ANTS'98-From Ant Colonies to Artificial Ants: First International Workshop on Ant Colony Optimization, 1998, Available online at: http://iridia.ulb.ac.be/ants98/ants98. html
10. Di Caro, G. and Dorigo, M., Two ant colony algorithms for best-effort routing in datagram networks. In Proceedings of the Tenth IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS '98), 541-546, 1998 (IASTED/ACTA Press).
11. Dorigo, M., Bonabeau, E. and Theraulaz, G., Ant algorithms and stigmergy. Future Generat. Comput. Systems, 2000, 16, 851-887.
12. Dorigo, M. and Di Caro, G., The ant colony optimization meta heuristic. In New Ideas in Optimization, edited by D. Come, M. Dorigo and F. Glover, 11-32, 1999 (McGraw-Hill: London).
13. Dorigo, M. and Gambardella, L.M., Ant colonies for the traveling salesman problem. BioSystems, 1997, 43, 73-81.
14. Dorigo, M., Maniezzo, V. and Colorni, A., The ant system: optimization by a colony of cooperating ants. IEEE Trans. Syst. Man Cybern., 1996, 26, 29-42.
15. Halhal, D., Walters, G.A., Ouazar, D. and Savic, D.A., Water network rehabilitation with structured messy genetic algorithm. J. Water Resour. Plan. Manag., 1997, 123(3), 137-146.
16. Lippai, I., Heany, J.P. and Laguna, M., Robust water system design with commercial intelligent search optimizers. J. Comput. Civ. Eng., 1999, 13(3), 135-143.
17. Maier, H.R., Simpson, A.R., Zecchin, A.C., Foong, W.K., Phang, K.Y., Seah, H.Y. and Tan, C.L., Ant colony optimization for design of water distribution systems. J. Water Resour. Plan. Manag., ASCE, 2003, 129(3), 200-209.
18. Savic, D.A. and Walters, G.A., Genetic algorithms for least-cost design of water distribution networks. Water Res. Plan. Manag., ASCE, 1997, 123(2), 67-77.
19. Stutzle, T. and Hoos, H.H., MAX-MIN ant system. Future Gener. Comput. Syst., 2000, 16, 889-914.
20. Walters, G. A., Halhal, D., Savic, D. and Quazar, D., Improved design of anytown distribution network using structured messy genetic algorithms. Urban Water, 1999, 1(1), 23-38.
21. Wu, Z.Y. and Simpson, A.R., A self-adaptive boundary search genetic algorithm and its application to water distribution systems. J. Water Res., 2002, 40(2), 191-203.
22. Zecchin, A.C., Maier, H.R., Simpson, A.R., Roberts, A., Berrisford, M.J. and Leonard, M., Max-min ant system applied to water distribution system optimization. Modsim 2003 - International Congress on Modelling and Simulation, Volume 1, pp. 795-800, 2003 (Modelling and Simulation Society of Australia and New Zealand Inc: Townsville, Australia).
23. Zheng, W., Boulos, P.F., Orr, C.H. and Ro, J.J., Using genetic algorithms to rehabilitate water distribution systems. J. AWWA, 2001, 93(11), 74-85.