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Erschienen in: Water Resources Management 10/2013

01.08.2013

Optimization of Water Resources Utilization by PSO-GA

verfasst von: Jian-xia Chang, Tao Bai, Qiang Huang, Da-wen Yang

Erschienen in: Water Resources Management | Ausgabe 10/2013

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Abstract

The objective of this paper is to present an optimal model to address the water resources utilization of the Tao River basin in China. The Tao River water diversion project has been proposed to alleviate the problem of water shortages in Gansu Province in China. A multi reservoir system is under consideration with multiple objectives including water diversion, ecological water demand, irrigation, hydropower generation, industrial requirements, and domestic uses in the Tao River basin. A multi-objective model for the minimization of water shortages and the maximization of hydro-power production is proposed to manage the utilization of Tao River water resources. An adjustable PSO-GA (particle swarm optimization – genetic algorithm) hybrid algorithm is proposed that combines the strengths of PSO and GA to balance natural selection and good knowledge sharing to enable a robust and efficient search of the solution space. Two driving parameters are used in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid algorithm by assigning a preference to either PSO or GA. The results show that the proposed hybrid algorithm can simultaneously obtain a promising solution and speed up the convergence.

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Literatur
Zurück zum Zitat Abd-El-Wahed WF, Mousa AA, El-Shorbagy MA (2011) Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems. J Comput Appl Math 235:1446–1453CrossRef Abd-El-Wahed WF, Mousa AA, El-Shorbagy MA (2011) Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems. J Comput Appl Math 235:1446–1453CrossRef
Zurück zum Zitat Chang NB, Wen CG, Chen YL, Yong YC (1996) A grey fuzzy multiobjective programming approach for the optimal planning of reservoir watershed. Part A. Theoretical development. Water Res 30:2329–2334CrossRef Chang NB, Wen CG, Chen YL, Yong YC (1996) A grey fuzzy multiobjective programming approach for the optimal planning of reservoir watershed. Part A. Theoretical development. Water Res 30:2329–2334CrossRef
Zurück zum Zitat Eberhart RC, Shi Y (1998) Comparison between genetic algorithms and particle swarm optimization. Evolutionary programming VII. Lect Notes Comput Sci 1447:611–6CrossRef Eberhart RC, Shi Y (1998) Comparison between genetic algorithms and particle swarm optimization. Evolutionary programming VII. Lect Notes Comput Sci 1447:611–6CrossRef
Zurück zum Zitat Fi-John C, Li C, Li-Chiu C (2005) Optimizing the reservoir operating rule curves by genetic algorithms. Hydrol Process 19:2277–2289CrossRef Fi-John C, Li C, Li-Chiu C (2005) Optimizing the reservoir operating rule curves by genetic algorithms. Hydrol Process 19:2277–2289CrossRef
Zurück zum Zitat Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading
Zurück zum Zitat Grygier TC, Stedinger JR (1985) Algorithms for optimizing hydropower system operation. Water Resour Res 21(1):1–10CrossRef Grygier TC, Stedinger JR (1985) Algorithms for optimizing hydropower system operation. Water Resour Res 21(1):1–10CrossRef
Zurück zum Zitat Hejazi MI, Cai X, Borah D (2008) Calibrating a watershed simulation model involving human interference – an application of multi-objective genetic algorithms. J Hydroinform 10(1):97–111CrossRef Hejazi MI, Cai X, Borah D (2008) Calibrating a watershed simulation model involving human interference – an application of multi-objective genetic algorithms. J Hydroinform 10(1):97–111CrossRef
Zurück zum Zitat Karamouz M, Vasiliadis H (1992) A Bayesian stochastic optimization of reservoir operation using uncertain forecast. Water Resour Res 28(5):1221–1232CrossRef Karamouz M, Vasiliadis H (1992) A Bayesian stochastic optimization of reservoir operation using uncertain forecast. Water Resour Res 28(5):1221–1232CrossRef
Zurück zum Zitat Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc. IEEE Int. Conf. Neural Networks, Perth, Australia, Dec: 1942–1948 Kennedy J, Eberhart R (1995) Particle swarm optimization. Proc. IEEE Int. Conf. Neural Networks, Perth, Australia, Dec: 1942–1948
Zurück zum Zitat Kucukmehmetogl M (2009) A game theoretic approach to assess the impacts of major investments on transboundary water resources: the case of the Euphrates and Tigris. Water Resour Manag 23(15):3069–3099. doi:10.1007/s11269-009-9424-3 CrossRef Kucukmehmetogl M (2009) A game theoretic approach to assess the impacts of major investments on transboundary water resources: the case of the Euphrates and Tigris. Water Resour Manag 23(15):3069–3099. doi:10.​1007/​s11269-009-9424-3 CrossRef
Zurück zum Zitat Labadie JW (2004) Optimal operation of multi-reservoir systems: state-of the-art review. J Water Resour Plan Manage, ASCE 130(2):93–111CrossRef Labadie JW (2004) Optimal operation of multi-reservoir systems: state-of the-art review. J Water Resour Plan Manage, ASCE 130(2):93–111CrossRef
Zurück zum Zitat Oliveira R, Loucks DP (1997a) Operating rules for multi-reservoir systems. Water Resour Res 33(4):839–852CrossRef Oliveira R, Loucks DP (1997a) Operating rules for multi-reservoir systems. Water Resour Res 33(4):839–852CrossRef
Zurück zum Zitat Oliveira R, Loucks DP (1997b) Operating rules for multi-reservoir systems. Water Resour Res 33(4):839–851CrossRef Oliveira R, Loucks DP (1997b) Operating rules for multi-reservoir systems. Water Resour Res 33(4):839–851CrossRef
Zurück zum Zitat Pereira MVF, Pinto LMVG (1985) Stochastic optimization of a multi-reservoir hydroelectric system: a decomposition approach. Water Resour Res 21(6):779–792CrossRef Pereira MVF, Pinto LMVG (1985) Stochastic optimization of a multi-reservoir hydroelectric system: a decomposition approach. Water Resour Res 21(6):779–792CrossRef
Zurück zum Zitat Reis LFR, Walters GA, Savic DE, Chaudhry FH (2005) Multi-reservoir operation planning using hybrid genetic algorithm and linear programming (GA-LP): an alternative stochastic approach. Water Resour Manag 19:831–848. doi:10.1007/s11269-005-6813-0 CrossRef Reis LFR, Walters GA, Savic DE, Chaudhry FH (2005) Multi-reservoir operation planning using hybrid genetic algorithm and linear programming (GA-LP): an alternative stochastic approach. Water Resour Manag 19:831–848. doi:10.​1007/​s11269-005-6813-0 CrossRef
Zurück zum Zitat Sharif M, Wardlaw R (2000) Multireservoir systems optimization using genetic algorithms: case study. J Comput Civ Eng 14(4):255–263CrossRef Sharif M, Wardlaw R (2000) Multireservoir systems optimization using genetic algorithms: case study. J Comput Civ Eng 14(4):255–263CrossRef
Zurück zum Zitat Sniedovich M (1979) Reliability-constrained reservoir control problems: 1. Methodological issues. Water Resour Res 15(6):1574–1582CrossRef Sniedovich M (1979) Reliability-constrained reservoir control problems: 1. Methodological issues. Water Resour Res 15(6):1574–1582CrossRef
Zurück zum Zitat Stedinger J, Sule B, Loucks D (1984) Stochastic dynamic programming models for reservoir operation optimization. Water Resour Res 20(11):1499–1505CrossRef Stedinger J, Sule B, Loucks D (1984) Stochastic dynamic programming models for reservoir operation optimization. Water Resour Res 20(11):1499–1505CrossRef
Zurück zum Zitat Su YS, Deininger RA (1974) Modeling regulation of Lake Superior under uncertainty of future water supplies. Water Resour Res 10(1):11–25CrossRef Su YS, Deininger RA (1974) Modeling regulation of Lake Superior under uncertainty of future water supplies. Water Resour Res 10(1):11–25CrossRef
Zurück zum Zitat Tejada-Guibert JA, Johnson SA, Stedinger JR (1995) The value of hydrologic information in stochastic dynamic programming models of a multireservoir system. Water Resour Res 31(10):2571–2579CrossRef Tejada-Guibert JA, Johnson SA, Stedinger JR (1995) The value of hydrologic information in stochastic dynamic programming models of a multireservoir system. Water Resour Res 31(10):2571–2579CrossRef
Zurück zum Zitat Torabi M, Mobasheri F (1974) A stochastic dynamic programming model for the optimum operation of a multipurpose reservoir. Water Resour Bull 9(6):1089–1099CrossRef Torabi M, Mobasheri F (1974) A stochastic dynamic programming model for the optimum operation of a multipurpose reservoir. Water Resour Bull 9(6):1089–1099CrossRef
Zurück zum Zitat Tung C, Hsu S, Liu C, Li J (2003) Application of the genetic algorithm for optimizing operation rules of the LiYuTan reservoir in Taiwan. J Am Water Resour Assoc 39(3):649–57CrossRef Tung C, Hsu S, Liu C, Li J (2003) Application of the genetic algorithm for optimizing operation rules of the LiYuTan reservoir in Taiwan. J Am Water Resour Assoc 39(3):649–57CrossRef
Zurück zum Zitat Uysal O, Bulkan S (2008) Comparison of genetic algorithm and particle swarm optimization for bicriteria permutation flowshop scheduling problem. Int J Comput Intell Res 4(2):159–175 Uysal O, Bulkan S (2008) Comparison of genetic algorithm and particle swarm optimization for bicriteria permutation flowshop scheduling problem. Int J Comput Intell Res 4(2):159–175
Zurück zum Zitat Wardlaw R, Sharif M (1999) Evaluation of genetic algorithms for optimal reservoir system operation. J Water Resour Plan Manage, ASCE 125(1):25–33CrossRef Wardlaw R, Sharif M (1999) Evaluation of genetic algorithms for optimal reservoir system operation. J Water Resour Plan Manage, ASCE 125(1):25–33CrossRef
Zurück zum Zitat Zhang X, Srinivasan R, Zhao K, Van Liew M (2009) Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model. Hydrolog Process 23:430–441CrossRef Zhang X, Srinivasan R, Zhao K, Van Liew M (2009) Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model. Hydrolog Process 23:430–441CrossRef
Metadaten
Titel
Optimization of Water Resources Utilization by PSO-GA
verfasst von
Jian-xia Chang
Tao Bai
Qiang Huang
Da-wen Yang
Publikationsdatum
01.08.2013
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 10/2013
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-013-0362-8

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