Optimising pump system with constant and variable speed pumps: case study

International Journal of Modelling, Identification and Control

Volumn 12, Issue 4, 2011, Pages 412-420

  Fang, Haien ^a   Wu, Wenyan ^b   Lv, Mou ^c   Gao, Jinliang ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b STAFFORDSHIRE UNIVERSITY   (United Kingdom)

^c QINGDAO TECHNOLOGICAL UNIVERSITY   (China)

Author keywords

mixed coding; MOEA; multi objective evolutionary algorithm; pump system; repair mechanism; water supply network

Indexed keywords

DECISION MAKING; PUMPS; REPAIR; WATER DISTRIBUTION SYSTEMS; WATER SUPPLY;

MIXED CODING; MOEA; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; PUMP SYSTEM; REPAIR MECHANISM; WATER SUPPLY NETWORKS;

EVOLUTIONARY ALGORITHMS;

EID: 79956150440     PISSN: 17466172     EISSN: 17466180     Source Type: Journal    
DOI: 10.1504/IJMIC.2011.040084     Document Type: Article

References (23)

1. Abido, M.A. (2006) 'Multiobjective evolutionary algorithms for electric power dispatch problem', IEEE Transactions on Evolutionary Computation, Vol. 10, No. 3, pp.315-329. (Pubitemid 43821761)
2. Barán, B., von Lücken, C. and Sotelo, A. (2004) 'Pump scheduling optimization using asynchronous parallel multiobjective evolutionary algorithms', CLEI Electronic Journal, Vol. 7, No. 2, pp.1-20.
3. Barán, B., von Lücken, C. and Sotelo, A. (2005) 'Multi-objective pump scheduling optimization using evolutionary strategies', Advances in Eng. Software, Vol. 36, No. 1, pp.39-47.
4. Carrijo, I.B., Fernanda, L., Reis, R. and Walters, G.A. (2004) 'Operational optimization of WDS based on multiobjective genetic algorithm and operational extraction rules using data mining', World Water and Environmental Resources Congress.
5. Deb, K. (2000) 'An efficient constraint handling method for genetic algorithms', Compute Methods Appl.Mech.Eng, Vol. 186, Nos. 2/4, pp.311-338.
6. Deb, K. (2003) 'A fast multi-objective evolutionary algorithm for finding well-spread pareto-optimal solutions', KanGAL Report No. 2003002.
7. Deb, K. and Jainz, S. (2002) 'Multi-speed gearbox design using multi-objective evolutionary algorithms', Tech. rep., KanGAL.
8. Deb, K., Pratap, A., Agrawal, S. et al. (2000) 'A fast and elitist multi-objective genetic algorithm: NSGA-II', KanGAL Report No. 200001, India.
9. El Hamdi, R., Njah, M. and Chtourou, M. (2008) 'Multilayer perceptron training using an evolutionary algorithm', International Journal of Modelling, Identification and Control, Vol. 5, No. 4, pp.305-312.
10. Gato, S., Jayasuriya, N. and Roberts, P. (2007) 'Forecasting residential water demand: case study', Journal of Water Resources Planning and Management, Vol. 133, No. 4, pp.309-319. (Pubitemid 47017922)
11. Ghiassi, M., Zimbra, D.K. and Saidane, H. (2008) 'Urban water demand forecasting with a dynamic artificial neural network model', Journal of Water Resources Planning and Management, Vol. 134, No. 2, pp.138-146. (Pubitemid 351279619)
12. Laumanns, M., Thiele, L., Deb, K. and Zitzler, E. (2002) 'Combining convergence and diversity in evolutionary multi-objective optimization', Evolutionary Computation, Vol. 10, No. 3, pp.263-282.
13. Lopez-Ibanez, M., Devi Prasad, T. and Paechter, B. (2005) 'Multi-objective optimization of the pump scheduling problem using SPEA2', Evolutionary Computation, The 2005 IEEE Congress, Vol. 1, pp.435-442. (Pubitemid 41495886)
14. Msiza, I.S., Nelwamondo, F.V. and Marwala, T. (2007) 'Artificial neural networks and support vector machines for water demand time series forecasting', Systems Man and Cybernetics ISIC IEEE International Conference on.
15. Pezeshk, S. and Helweg, O.J. (1996) 'Adaptive search optimization in reducing pump operating costs', Journal of Water Resources Planning and Management, Vol. 122, No. 1, pp.57-63.
16. Sakawa, M., Yano, H. and Yumine, T. (1987) 'An interactive fuzzy satisfying method for multiobjective linear programming problems and its applications', IEEE Trans.Syst. Man, Cybern, Vol. SMC-17, No. 4, pp.654-661. (Pubitemid 17650834)
17. Savic, D.A., Walters, G.A. and Schwab, M. (1997) 'Multiobjective genetic algorithms for pump scheduling in water supply', AISB International Workshop on Evolutionary Computing, Lecture Notes in Computer Science, Vol. 1305, pp.227-236, Berlin. (Pubitemid 127147220)
18. Schott, J.R. (1995) 'Fault tolerant design using single and multicriteria genetic algorithm optimization', Master's thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology.
19. Soukkou, A., Khellaf, A. and Leulmi, S. (2007) 'Multiobjective optimisation of robust Takagi-Sugeno fuzzy neural controller with hybrid learning algorithm', International Journal of Modelling, Identification and Control, Vol. 2, No. 4, pp.332-346.
20. Van Veldhuizen, D.A. and Lamout, G.B. (1999) 'Multi-objective evolutionary algorithms: classifications, analysis, and new innovations', PhD thesis, Department of Electrical and Computer Engineering, Graduate school of Engineering, Air Force Institute of Technology, Wright-Patterson AFB, Ohio.
21. Xin, J., Wu, W.Y. and Gao, J. (2008) 'Optimal placement of pressure monitors in water supply network with elitist genetic algorithm', International Journal of. Modelling, Identification and Control, Vol. 4, No. 2, pp.68-75.
22. Zitzler, E. (1999) 'Evolutionary algorithms for multiobjective optimization: methods and applications', PhD thesis, Swiss federal institute of technology (ETH), Zurich, Switzerland.
23. Zitzler, E., Laumanns, M. and Thiele, L. (2001) 'SPEA2: Improving the strength pareto evolutionary algorithm', TIK-Report 103.