Multiobjective Planning of Surface Water Resources by Multiobjective Genetic Algorithm with Constrained Differential Dynamic Programming
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 6
Abstract
Owing to the conflict encountered between the two objectives of fixed cost in reservoir installation and operating cost in time-varying water deficit, multiobjective planning of surface water resources is a difficult job. Instead of combining these two objectives into just one objective using the weighting factor approach, this investigation proposes a novel method by integrating a multiobjective genetic algorithm (MOGA) with constrained differential dynamic programming (CDDP). A MOGA is employed to generate the various combinations of reservoir capacity and estimate the noninferior solution set. However, applying this algorithm to solve the dynamics of the operating cost, the number of variables increasing with time will dramatically increase the use of computational resources. Consequently, the CDDP is herein adopted to distribute optimal releases among reservoirs to satisfy water demand as much as possible. Next, the effectiveness of the proposed methodology is verified by solving a multiobjective planning problem of surface water in southern Taiwan. This real application demonstrates that MOGA can be linked with CDDP to resolve a complex water resources problem. Additionally, the ability of MOGA on addressing multiple objectives simultaneously without converting to a weighted objective function provides the opportunity for significant advancement in multiobjective optimization. Finally, this investigation also proposes three suitable strategies of reservoir construction to decision makers with budget concerns through the analysis of all noninferior solutions.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers would like to thank the National Science Council of the Republic of China for financially supporting this research under Contract No. NSC 90-2211-E-009-061. Appreciation also goes to Erik Avasalu, an English native speaker and current graduate student of Graduate Institute of Translation and Interpretation National Taiwan Normal University, for assistance in improving the English language in this paper.
References
Burn, D. H., and Yulianti, J. S. (2001). “Waste-load allocation using genetic algorithms.” J. Water Resour. Plann. Manage., 127(2), 121–129.
Chang, L. C., Shoemaker, C. A., and Liu, P. L. F. (1992). “Optimal time-varying pumping rates for groundwater remediation: Application of a constrained optimal control algorithm.” Water Resour. Res., 28(12), 3157–3171.
Chang, L. C., and Yang, C. C. (2002). “Optimizing the rule curves for multi-reservoir operations using a genetic algorithm and HEC-5.” J. Hydrosci. Hydr. Eng., 20(1), 59–75.
Cieniawski, S. E., Eheart, J. W., and Ranjithan, S. (1995). “Using genetic algorithm to solve a multiobjective groundwater monitoring problem.” Water Resour. Res., 31(2), 399–409.
Goldberg, D. E. (1989). Genetic algorithm in search, optimization, and machine learning, Addison-Wesley, Reading, Mass.
Hirad, M., and Ramamurthy, A. S. (2000). “Optimal design of multi-reservoir systems for water supply.” Adv. Water Resour., 23, 613–624.
Hsiao, C.-T., and Chang, L.-T. (2002). “Dynamic optimal groundwater management with inclusion of fixed costs.” J. Water Resour. Plann. Manage., 128(1), 57–65.
Hsu, S.-K. (1995). “Shortage indices for water-resources planning in Taiwan.” J. Water Resour. Plann. Manage., 121(2), 119–131.
Hydrologic Engineering Center (HEC). (1966). Reservoir yield, generalized computer program 23-J2-L245, U.S. Army, Corps of Engineers, Davis, Calif.
Hydrologic Engineering Center (HEC). (1975). Hydrologic engineering methods for water resources development, Vol. 8, U.S. Army, Corps of Engineers, Davis, Calif.
Khaliquzzaman, and Chander, S. (1997). “Network flow programming model for multireservoir sizing.” J. Water Resour. Plann. Manage., 123(1), 15–22.
Kim, T., and Heo, J.-H. (2004). “Multi-reservoir system optimization using multi-objective genetic algorithms.” World Water and Environmental Resources Congress, Salt Lake City.
Labadie, J. W. (2004). “Optimal operation of multireservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage., 130(2), 93–111.
Murray, D. M., and Yakowitz, S. J. (1981). “The application of optimal control methodology to nonlinear programming problems.” Math. Program., 21(3), 331–347.
Prasad, T. D., and Park, N.-S. (2004).“Multiobjective genetic algorithms for design of water distribution networks.” J. Water Resour. Plann. Manage., 130(1), 73–82.
Water Resources Planning Commission. (1986). Estimation of water supply requirements in Tainan, Kaohsiung, and Pintung areas, Taipei, Taiwan.
Watkins, D. W., Jr., and McKinney, D. C. (1998). “Decomposition methods for water resources optimization models with fixed costs.” Adv. Water Resour., 21(4), 283–295.
Wu, H. R. (1997). “A study on the relationship between development cost of water resources and water price.” Proc., 1997 Conf. of Rational Water Usage and Production, Hsinchu, Taiwan, 41–48.
Yakowitz, S. J. (1986). “The stagewise Kuhn-Tucker condition and differential dynamics programming.” IEEE Trans. Autom. Control, 31(1), 25–30.
Yeh, C.-H., and Labadie, J. W. (1997). “Multiobjective watershed-level planning of storm-water detention systems.” J. Water Resour. Plann. Manage., 123(6), 336–343.
You, J. J., Gan, H., and Wang, H. (2004). “New method for multi-objective problem based on genetic algorithm and its application in reservoir operation.” 6th Int. Conf. on Hydro-Informatics, Singapore, 969–976.
Information & Authors
Information
Published In
Copyright
© 2007 ASCE.
History
Received: Dec 23, 2004
Accepted: Sep 11, 2006
Published online: Nov 1, 2007
Published in print: Nov 2007
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.