Ant Colony Optimization Algorithms for Optimal Operation of Reservoirs: A Comparative Study of Four Algorithms

Document Type : پژوهشی

Authors

• M.H. Afshar
• S.E. Rezaee
• R. Moeini

10.22067/civil.v25i2.40651

Abstract

Optimal operation of reservoir is one of the most important problems of water resource engineering addressed by many researchers. Mathematical and traditional optimization methods have been extensively used to solve reservoir operation problem. Nowadays, meta-heuristics methods such as Ant Colony Optimization (ACO) algorithms, however, are being used more and more to solve this problem. ACO algorithms refer to a family of search methods based on the foraging behavior of real ant colonies. In this paper, the application of four ACO algorithms namely, Ant System, Elitist Ant System, Ranked Ant System and Max-Min Ant System is used to solve the simple and hydropower reservoir operation problems. The efficiency of these methods is tested against the benchmark example of "Dez" reservoir and the results are presented and compared. The results indicate the superiority of Max-Min Ant System over other algorithms to solve reservoir operation problem.

Keywords

• Meta-Heuristic Algorithm
• Ant Colony Optimization Algorithm
• Optimal Operation of Reservoir

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References

1. Colorni, A., Dorigo, M., Maffoli, F., Maniezzo, V., Righini, G. and Trubian, M., "Heuristics from nature for hard combinatorial optimization problems", International Transactions on Operational Research, 3, pp. 1-21, (1997).

2. Colorni, A., Dorigo, M. and Maniezzo, V., "Ant System: An autocatailytic optimizing process", Tech.Report 91-016, Politecnico di Milano, Italy, (1991).

3. Dorigo, M., and Gambardella, L.M., "Ant colonies for traveling salesman problem", BioSystem, 43, pp. 73-81, (1997a).

4. Stutzle, T. and Hoos, H.H., "Max-Min Ant system", Future Generation Computer System, 16(9), pp. 889-914, (2000).

5. Bullnheimer, B., Hartl, R.F. and Strauss, C., "A new rank-based version of the ant system: A computational study", Central European Journal for Operations Research and Economics, 7(1), pp. 25-38, (1999).

6. Cordon, O., Fernandez de Viana, I., Herrena, F. and Moreno, L., "A new ACO model integrating evolutionary computation concepts: the best-worst ant system", In Proceedings of ANTS'2000-From Ant Colonies to Artificial Ants: Second International Workshop on Ant Algorithms, Brussels, Belgium, pp. 22-29, (2000).

7. Gambardella, L.M, and Dorigo, M., "An ant colony system hybridized with a new local search for the sequential ordering problem", INFORMS Journal on Computing, 12(3), pp. 237-255, (2000).

8. Ali, M., Pant, M. and Abraham, A., "A hybrid ant colony differential evolution and its application to water resources problems", Proceedings of the 2009 Nature & Biologically Inspired Computing World Congress, Coimbatore, India, pp. 1133 – 1138, (2009).

9. Chandra Mohan, B. and Baskaran, R., "A survey: Ant Colony Optimization based recent research and implementation on several engineering domain", Expert Systems with Applications, 39, pp. 4618–4627, (2012).

10. Ostfeld, A., "Ant Colony Optimization for Water Resources Systems Analysis – Review and Challenges", Ant Colony Optimization - Methods and Applications, chapter 17, Published by InTech, (2011).

11. Stutzle, T., Lopez-Ibañez, M. and Dorigo, M., "Concise Overview of Applications of Ant Colony Optimization", Wiley Encyclopedia of Operations Research and Management Science, John Wiley & Sons Inc, pp. 896-911, (2011).

12. Abbaspour, K.C., Schulin, R. and Van Genuchten, M.T., "Estimating unsaturated soil hydraulic parameters using ant colony optimization", Adv. water resource., 24(8), pp. 827-841, (2001).

13. Simpson, A.R., Maier, H.R., Foong, W.K., Phang, K.Y., Seah, H.Y. and Tan, C.L., "Selection of parameters for ant colony optimization applied to the optimal design of water distribution systems", Proc. Int. Congress on Modeling and Simulation, Canberra, Australia, pp. 1931-1936, (2001).

14. 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 system", J. Water Resour. Plng. and Mgmt., 129(3), pp. 200-209, (2003).

15. Zecchin, A.C., Simpson, A.R., Maier, H.R., Leonard, M., Roberts, A. and Berrisford, M.J., "Application of two ant colony optimisation algorithms to water distribution system optimization", Mathematical and Computer Modeling, 44, pp. 451-468, (2005).

16. Afshar, M.H., "Application of Max-Min ant algorithm to joint layout and size optimization of pipe network", Engineering optimization, 38(3), pp. 299-317, (2006).

17. Afshar, M.H., "Improving the efficiency of ant algorithms using adaptive refinement: Application to storm water network design", Advances in Water Resources, 29(9), pp. 1371-1382, (2006).

18. Afshar, M.H., and Moeini, R., "Partially and Fully Constrained Ant Algorithms for the Optimal Solution of Large Scale Reservoir Operation problems", J. Water Resour. Manage, 22(1), pp. 1835-1857, (2008).

19. Ostfeld, A. and Tubaltzev, A., "Ant colony optimization for least cost design of water distribution systems", Journal of Water Resources Planning and Management Division, ASCE, 134(2), pp. 107-118, (2008).

20. Afshar, A., Abbasi, H. and Jalali, M.R., "Optimum Design of Water Conveyance Systems by Ant Colony Optimization Algorithms", International Journal of Civil Engineering, 4(1), pp. 1-13, (2006).

21. Afshar, M.H., "Layout and size optimization of tree-like pipe networks by incremental solution ants", Can. J. civ. Eng., 35, pp. 129-139, (2008).

22. Afshar, M.H., "Elitist-Mutated Ant System Versus Max-Min Ant System: Application to Pipe Network Optimization Problems", SCIENTIA IRANICA, Transaction A: Civil Engineering, 16(4), pp. 286-296, (2009).

23. Madadgar, S. and Afshar, A., "An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems", Water Resource Management, 23(10), pp. 2119–2139, (2009).

24. Afshar, M.H., "A parameter free continuous Ant Colony Optimization Algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach", Advances in Engineering Software, 41, pp. 188–195, (2010).

25. Abbasi, H., Afshar, A. and Jalali, M.R., "Ant-colony-based simulation–optimization modeling for the design of a forced water pipeline system considering the effects of dynamic pressures", Journal of Hydroinformatics, 12(2), pp. 212-224, (2010).

26. Madadgar, S. and Afshar, A., "Forced Water main design; mixed ant colony optimization", Int. J. Optim. Civil Eng., 1, pp. 47-71, (2011).

27. Moeini, R. and Afshar, M.H., "Layout and size optimization of Sanitary Sewer network using intelligent ants", Advances in Engineering Software, 51, pp. 49-62, (2012).

28. Moeini, R. and Afshar, M.H., "Constrained Ant Colony Optimization Algorithm for the layout and size optimization of sanitary sewer networks", Urban Water journal, 10(3), pp. 154-173, (2013).

29. Grasse, p.p., "La reconstruction dun id et les coordinations inter-individuelles chez., Bellicositermes natalensis et Cubitermes sp. La theorie de la stigmergie: essai d’interpretation du comportement des termites constructeurs. " Insectes Soc., 6, pp. 41–81,in Portuguese, (1959).

30. Manielzo, V. and Colorni, A., "The ant system: optimization by a colony of cooperating ants", IEEE Trans. Syst Man. Cybern., 26(1), pp. 29-42, (1996).

31. Dorigo, M., and Gambardella, L.M., "Ant colony system: A cooperaive learning approach to the traveling salesman problem", IEEE Transactions on Evolutionary Computation, 1(1), pp. 53-66, (1997).

32. Winston, W. L., "Introduction to mathematical programming: application and algorithms", Duxbury Press, Belmont, CA., (1995).

33. Jalali, M.R., "Optimal design and operation of hydro systems using Ant Colony Algorithm: A new meta heuristic approach", PhD Thesis, Iran University Science and Technology, (2005).