Representations and evolutionary operators for the scheduling of pump operations inwater distribution networks

Evolutionary Computation

Volumn 19, Issue 3, 2011, Pages 429-467

  López Ibáñez, Manuel ^a   Devi Prasad, T ^b   Paechter, Ben ^c  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

^b UNIVERSITY OF SALFORD   (United Kingdom)

^c EDINBURGH NAPIER UNIVERSITY   (United Kingdom)

Author keywords

Evolutionary operators; Genetic algorithms; Pump scheduling; Representation; Water distribution networks

Indexed keywords

BINARY REPRESENTATIONS; BINARY VALUES; EMPIRICAL RESULTS; EVOLUTIONARY OPERATORS; EXPLICIT REPRESENTATION; FEASIBLE REGIONS; HYBRID GENETIC ALGORITHMS; NUMBER OF SWITCHES; PUMP OPERATION; PUMP SCHEDULING; RECENT STATE; REPRESENTATION; TIME INTERVAL; WATER DISTRIBUTION NETWORKS;

ENERGY UTILIZATION; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; SCHEDULING ALGORITHMS; TIME SWITCHES; WATER DISTRIBUTION SYSTEMS;

PUMPS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPARATIVE STUDY; COMPUTER SIMULATION; INFORMATION SYSTEM; THEORETICAL MODEL; WATER SUPPLY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; MANAGEMENT INFORMATION SYSTEMS; MODELS, THEORETICAL; WATER SUPPLY;

EID: 80051487228     PISSN: 10636560     EISSN: 15309304     Source Type: Journal    
DOI: 10.1162/EVCO_a_00035     Document Type: Article

References (44)

1. Atkinson, R., van Zyl, J. E., Walters, G. A., and Savic, D. A. (2000). Genetic algorithm optimisation of level-controlled pumping station operation. Water network modelling for optimal design and management (pp. 79-90). Exeter, UK: Centre for Water Systems.
2. Chase, D. V., and Ormsbee, L. E. (1993). Computer-generated pumping schedules for satisfying operation objectives. Journal of the American Water Works Association, 85(7), 54-61.
3. Cohen, G. (1982). Optimal control of water supply networks. In S. G. Tzafestas (Ed.), Optimization and control of dynamic operational research models, Vol. 4 (pp. 251-276). Amsterdam: North-Holland.
4. Dandy, G. C., and Gibbs, M. S. (2003). Optimizing system operations and water quality. In P. Bizier and P. DeBarry (Eds.), Proceedings ofWorldWater and Environmental Resources Congress. Philadelphia: ASCE.
5. Dean, A., and Voss, D. (1999). Design and analysis of experiments. Berlin: Springer.
6. Deb, K. (2000). An efficient constraint handlingmethod for genetic algorithms. ComputerMethods in Applied Mechanics and Engineering, 186(2-4):311-338.
7. Eshelman, L. J., and Schaffer, J. D. (1992). Real-coded genetic algorithms and interval-schemata. In L. D. Whitley (Ed.), FOGA, pp. 187-202.
8. Farmani, R., Walters, G. A., and Savic, D. A. (2006). Evolutionary multi-objective optimization of the design and operation of water distribution network: Total cost vs. reliability vs. water quality. Journal of Hydroinformatics, 8(3):165-179.
9. Fogel, D. B. (1995). Evolutionary computation. Toward a new philosophy of machine intelligence. Piscataway, NJ: IEEE Press.
10. Goldman, F. E., and Mays, L. W. (2000). The application of simulated annealing to the optimal operation of water systems. In Proceedings of 26th Annual Water Resources Planning and Management Conference.
11. Herrera, F., Lozano, M., and Sánchez, A. M. (2003). A taxonomy for the crossover operator for real-coded genetic algorithms: An experimental study. International Journal of Intelligent Systems, 18(3):309-338.
12. Jowitt, P.W., and Germanopoulos, G. (1992). Optimalpumpscheduling in water supply networks. Journal of Water Resources Planning and Management, ASCE, 118(4):406-422.
13. Kazantzis, M. D., Simpson, A. R., Kwong, D., and Tan, S. M. (2002). A new methodology for optimizing the daily operations of a pumping plant. In Proceedings of the 2002 Conference on Water Resources Planning.
14. Lansey, K. E., and Awumah, K. (1994). Optimal pump operations considering pump switches. Journal of Water Resources Planning and Management, ASCE, 120(1):17-35.
15. Leon, C., Martin, S., Elena, J. M., and Luque, J. (2000). EXPLORE: Hybrid expert system for water networks management. Journal of Water Resources Planning and Management, ASCE, 126(2):65-74.
16. López-Ibáñez, M. (2009). Operational optimisation of water distribution networks. PhD thesis, School of Engineering and the Built Environment, Edinburgh Napier University, UK.
17. López-Ibáñez, M., Prasad, T. D., and Paechter, B. (2008). Ant colony optimisation for the optimal control of pumps in water distribution networks. Journal of Water Resources Planning and Management, ASCE, 134(4):337-346.
18. Mäckle, G., Savic, D. A., and Walters, G. A. (1995). Application of genetic algorithms to pump scheduling for water supply. In Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA'95, Vol. 414, pp. 400-405.
19. Maier, H. R., Simpson, A. R., Zecchin, A. C., Foong, W. K., Phang, K. Y., Seah, H. Y., and Tan, C. L. (2003). Ant colony optimization for design of water distribution systems. Journal of Water Resources Planning and Management, ASCE, 129(3):200-209.
20. McCormick, G., and Powell, R. S. (2003a). Optimal pump scheduling in water supply systems withmaximum demand charges. Journal ofWater Resources Planning andManagement, ASCE, 129(5):372-379.
21. McCormick, G., and Powell, R. S. (2003b). A progressive mixed integer-programming method for pump scheduling. In C. Maksimović, D. Butler, and F. A. Memon (Eds.), Proceedings of Advances in Water Supply Management, pp. 307-313.
22. McCormick, G., and Powell, R. S. (2004). Derivation of near-optimal pump schedules for water distribution by simulated annealing. Journal of the Operational Research Society, 55(7):728-736.
23. Michalewicz, Z. (1996). Genetic algorithms Data structures Evolution programs (3rd Ed.). Berlin: Springer.
24. Michalewicz, Z., Dasgupta, D., Riche, R. G. L., and Schoenauer, M. (1996). Evolutionary algorithms for constrained engineering problems. Computers and IndustrialEngineering, 30(4):851-870.
25. Mühlenbein, H., and Schlierkamp-Voosen, D. (1993). Predictive models for the breeder genetic algorithm. Evolutionary Computation, 1(1):25-49.
26. Nitivattananon, V., Sadowski, E. C., and Quimpo, R. G. (1996). Optimization of water supply system operation. Journal ofWater Resources Planning andManagement, ASCE, 122(5):374-384.
27. Ormsbee, L. E., and Lansey, K. E. (1994). Optimal control of water supply pumping systems. Journal of Water Resources Planning and Management, ASCE, 120(2):237-252.
28. Ormsbee, L. E., and Reddy, S. L. (1995). Nonlinear heuristic for pump operations. Journal ofWater Resources Planning and Management, ASCE, 121(4):302-309.
29. Pezeshk, S., and Helweg, O. J. (1996). Adaptative search optimisation in reducing pump operation costs. Journal of Water Resources Planning and Management, ASCE, 122(1):57-63.
30. Prasad, T. D. (2009). Design of pumped water distribution networks with storage. Journal ofWater Resources Planning and Management, ASCE, 136(4):129-136.
31. Rao, Z., and Salomons, E. (2007). Development of a real-time, near-optimal control process for water-distribution networks. Journal of Hydroinformatics, 9(1):25-37.
32. Rossman, L. A. (1999). The EPANET programmer's toolkit for analysis of water distribution systems. In Proceedings of the Annual Water Resources Planning and Management Conference.
33. Rossman, L. A. (2000). EPANET 2 users' manual. Cincinnati, OH: U.S. Environmental Protection Agency.
34. Sakarya, A. B. A., and Mays, L.W. (2000). Optimal operation of water distribution pumps considering water quality. Journal of Water Resources Planning and Management, ASCE, 126(4):210-220.
35. Savic, D. A., Walters, G. A., and Schwab, M. (1997). Multiobjective genetic algorithms for pump scheduling in water supply. In D. Corne and J. L. Shapiro (Eds.), Evolutionary Computing Workshop, AISB'97, Vol. 1305 of Lecture Notes in Computer Science, pp. 227-236. Berlin: Springer-Verlag.
36. Sheskin, D. J. (2000). Handbook of parametric and nonparametric statistical procedures (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC.
37. Sotelo, A., von Lücken, C., and Barán, B. (2002). Multiobjective evolutionary algorithms in pump scheduling optimisation. In B. H. V. Topping and Z. Bittnar (Eds.), Proceedings of the Third International Conference on Engineering Computational Technology. Stirling, Scotland: Civil-Comp Press.
38. Ting, T.-O., Rao, M., Loo, C., and Ngu, S. (2003). Solving unit commitment problem using hybrid particle swarm optimization. Journal of Heuristics, 9(6):507-520.
39. van Zyl, J. E. (2001). A methodology for improved operational optimization of water distribution systems. PhD thesis, School of Engineering and Computer Science, University of Exeter, UK.
40. van Zyl, J. E., Savic, D. A., and Walters, G. A. (2004). Operational optimization of water distribution systems using a hybrid genetic algorithm. Journal of Water Resources Planning and Management, ASCE, 130(2):160-170.
41. Vasan, A., and Simonovic, S. P. (2010). Optimization of water distribution network design using differential evolution. Journal ofWater Resources Planning andManagement, ASCE, 136(2):279-287.
42. Walski, T. M., Chase, D. V., Savic, D. A., Grayman, W., Beckwith, S., and Koelle, E. (2003). Advanced water distribution modeling and management. Waterbury, CT: Haestad Press.
43. Wegley, C., Eusuff, M., and Lansey, K. E. (2000). Determining pump operations using particle swarm optimization. In R. H. Hotchkiss and M. Glade (Eds.), Building Partnerships, Proceedings of the Joint Conference on Water Resources Engineering and Water Resources Planning and Management. Available at http://dx.doi.org/10.1061/40517(2000)206.
44. Yu, G., Powell, R. S., and Sterling, M. J. H. (1994). Optimized pump scheduling in water distribution systems. Journal of Optimization Theory and Applications, 83(3):463-488.