Multi-Reservoir Operation Planning Using Hybrid Genetic Algorithm and Linear Programming (GA-LP): An Alternative Stochastic Approach

Reis, Luisa Fernanda Ribeiro; Walters, Godfrey A.; Savić, Dragan; Chaudhry, Fazal Hussain

doi:10.1007/s11269-005-6813-0

Cited by 44 publications

(35 citation statements)

References 11 publications

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“…(CV R ) j = maxf(TCH P j ); 0:0g; (12) and and are penalty coe cients for operational and reliability constraints, respectively. Application of CA to any optimization problem requires four primary components of the CA model, namely, cells, cell state, cell neighborhood, and the transition or updating rule, to be de ned.…”

Section: Proposed Adaptive Relaxed Cellularmentioning

confidence: 99%

“…Many di erent forms of reservoir operation problems have been solved by genetic algorithm [9][10][11][12]. Ant Colony Optimization (ACO) [13,14], Particle Swarm Optimization (PSO) [15], Simulated Annealing (SA) [16,17], and Honey Bees Mating Optimization (HBMO) [18] have also been suggested and used to achieve optimal operating policies for reservoir systems.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

Azizipour

Afshar

2017

Scientia Iranica

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Abstract. This paper presents a novel cellular automata Approach as the solution to reliability-based reservoir hydropower operation problems. The method is based on the observation that a low value of the penalty parameter would lead to partial enforcement of the constraints. Therefore, in this method, the constraints of the chance-constrained operation problem, namely operational and reliability constraints, are dealt with di erently. A high enough value of the penalty parameter is used for the rst set while a lower than enough value is used for the second set, leading to strong enforcement of the rst set of the constraint and partial ful llment of the second set. Since the proper value of the penalty parameter to be used for the reliability constraints is not known a priori, an adaptive method is proposed to nd the proper value. The proposed model is used for operation of Dez reservoir in Iran and the results are presented and compared with those of a Genetic Algorithm. Hydropower operation is considered over short, medium, and long-term periods to demonstrate the e ciency and e ectiveness of the proposed method for problems of di erent scales. The proposed model has proven to produce results superior to the results of GA with much reduced computational e ort.

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Section: Proposed Adaptive Relaxed Cellularmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

Azizipour

Afshar

2017

Scientia Iranica

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“…Application of hybrid algorithms for optimum design and/or operation of water resources problems have a fairly recent origin (Cai et al 2001;Reis et al 2005Reis et al , 2006. Combination of metaheuristic and/or evolutionary algorithms with a LP model for decomposition and two stage solutions of highly non-linear and large scale water resources problems have been quite satisfactory (Afshar et al 2010).…”

Section: Proposed Hybrid Decomposition Aco-lp Algorithmmentioning

confidence: 99%

“…To relax the drawbacks of common MINLP solvers and realizing the computational advantages of hybrid models in dealing with large NP-hard MINLP problems (Afshar et al 2009a, b;Reis et al 2005 and; this paper presents a hybrid (ACO-LP) model for direct minimization of reservoir capacity with reliability constraints. Reliability constraints are embedded into the modeling framework to eliminate iterative procedures in reliability-based…”

mentioning

confidence: 99%

Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm

Afshar

Masoumi

Solis

2015

Water Resour Manage

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Optimal design of irrigation and water supply reservoirs under reliability constraints may be categorized as large combinatorial optimization problems. In this paper, the reliability based optimum design of a single water supply reservoir is formulated as a mixed integer programming and a hybrid algorithm is introduced for its solution. To eliminate iterative procedures in reliability-based reservoir design and operation, the reliability requirements are directly embedded into the modeling framework and treated as different sets of constraints. Adaptive penalty method is used for constraint handling in the solution methodology. The proposed algorithm couples an ant colony optimization (ACO) optimizer with a virtual linear programing (LP) model for the solution of the resulted NP-hard mixed integer nonlinear programming problem. Dez reservoir for irrigation water supply with 480 months of inflow is used to demonstrate the method and its performance. The structure and solution methodology is verified by the solution to the inverse problem. It is shown that the proposed hybrid model can efficiently solve the problem for various combinations of reliability measures in a multiple period modeling scheme. It is illustrated that under some circumstances and specific reliability values, the mixed integer nonlinear programming (MINLP) solver may even fail to address a feasible and local optimal solution. Although operating rule is not included in the operational scheme, the procedure is capable of identifying coefficients for decision rules with any proposed structure.

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“…Juran Ali Ahmed and Arup kumar Sarma [11] have demonstrated genetic algorithm model for finding the optimal operating policy of a multipurpose reservoir. Multireservoir operation planning using hybrid GA and linear programming have been presented by Reis et al [12].They have proposed a new approach using GA and LP to determine operational decisions for reservoirs of a hydro system throughout a planning period, with the possibility of considering a variety of equally likely hydrologic sequences representing inflows. Jothiprakash and Ganeshan Shanthi [13] have developed GA model and applied to Pechiparai reservoir in Tamil Nadu, India to derive the optimal operational strategies.…”

Section: Introductionmentioning

confidence: 99%

Multi Objective Multireservoir Optimization in Fuzzy Environment for River Sub Basin Development and Management

Regulwar¹,

Raj²

2009

JWARP

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In this paper, a multi objective, multireservoir operation model is proposed using Genetic algorithm (GA) under fuzzy environment. A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFU-OPT) model for the present study is developed in 'C' Language. The GA parameters i.e. population size, number of generations, crossover probability, and mutation probability are decided based on optimized values of fitness function. The GA operators adopted are stochastic remainder selection, one point crossover and binary mutation. Initially the model is run for maximization of irrigation releases. Then the model is run for maximization of hydropower production. These objectives are fuzzified by assuming a linear membership function. These fuzzified objectives are simultaneously maximized by defining level of satisfaction () and then maximizing it. This approach is applied to a multireservoir system in Godavari river sub basin in Maharashtra State, India. Problem is formulated with 4 reservoirs and a barrage. The optimal operation policy for maximization of irrigation releases, maximization of hydropower production and maximization of level of satisfaction is presented for existing demand in command area. This optimal operation policy so determined is compared with the actual average operation policy for Jayakwadi Stage-I reservoir.

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Multi-Reservoir Operation Planning Using Hybrid Genetic Algorithm and Linear Programming (GA-LP): An Alternative Stochastic Approach

Cited by 44 publications

References 11 publications

An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm

Multi Objective Multireservoir Optimization in Fuzzy Environment for River Sub Basin Development and Management

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