1998
DOI: 10.1111/j.1752-1688.1998.tb04133.x
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COMPUTATIONAL IMPROVEMENT FOR STOCHASTIC DYNAMIC PROGRAMMING MODELS OF URBAN WATER SUPPLY RESERVOIRS1

Abstract: This paper describes two methods that are introduced to improve the computational effort of stochastic dynamic programming (SDP) as applicable to the operation of multiple urban water supply reservoir systems. The stochastic nature of streamflow is incorporated explicitly by considering it in the form of a multivariate probability distribution. The computationally efficient Gaussian Legendre quadrature method is employed to compute the conditional probabilities of streamflow, which accounts for the serial corr… Show more

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Cited by 10 publications
(5 citation statements)
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“…Some of the variations of DP that were used for overcoming dimensionality problem/curse of dimensionality are: State increment DP (Larson 1968), Incremental DP (Hall et al 1969), Differential DP (Jacobson and Mayne 1970), Discrete Differential DP (Heidari et al 1971), constraint differential DP (Murray and Yakowitz 1979), progressive optimality (Turgeon 1981), and binary state DP (Ozden 1984). Perera and Codner (1998) successfully improved the computational efficiency of SDP method when applied to multiple reservoir urban water supply system. For example, In DDDP, an initial feasible trial trajectory is essential to start the process of iteration.…”
Section: Improvements In Dynamic Programming To Overcome Curse Of Dimmentioning
confidence: 99%
“…Some of the variations of DP that were used for overcoming dimensionality problem/curse of dimensionality are: State increment DP (Larson 1968), Incremental DP (Hall et al 1969), Differential DP (Jacobson and Mayne 1970), Discrete Differential DP (Heidari et al 1971), constraint differential DP (Murray and Yakowitz 1979), progressive optimality (Turgeon 1981), and binary state DP (Ozden 1984). Perera and Codner (1998) successfully improved the computational efficiency of SDP method when applied to multiple reservoir urban water supply system. For example, In DDDP, an initial feasible trial trajectory is essential to start the process of iteration.…”
Section: Improvements In Dynamic Programming To Overcome Curse Of Dimmentioning
confidence: 99%
“…In this way, large and complex problems can be theorefically solved by combining the solufions of smaller problems (sub-problems) to obtain fhe solufion of the entire problem (Mays & Tung 2002). Applicafions of DP in the water resources area was discussed by Yakowitz (1982) and Yeh (1985) while more recent applicafions of DP and its variants in reservoir operations were presented by Perera & Conder (1998), Kimiar & Baliarsingh (2003), and Mousavi & Karamouz (2003).…”
Section: Introductionmentioning
confidence: 98%
“…Yeh (1985) reviewed a number of approaches to reservoir operation and described the state of the art at that time. Since then, dynamic programming (DP) and its variants have been explored and frequently recommended to determine the optimal operating strategy for a multipurpose and/or multireservoir system (Kelman et al, 1990;Thomas et al, 1997;Perera and Codner, 1998;Chang et al, 2002;Chandramouli et al, 2002). More recently, fuzzy logic has been highly recommended for modelling reservoir operation to solve the inherent imprecision and vagueness characteristics in reservoirs.…”
Section: Introductionmentioning
confidence: 98%