Dynamic programming integrated particle swarm optimization algorithm for reservoir operation

The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle Swarm Optimization (PSO). The reservoi...

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Vydáno v:International journal of system assurance engineering and management Ročník 11; číslo 2; s. 515 - 529
Hlavní autoři: Bilal, Rani, Deepti, Pant, Millie, Jain, S. K.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New Delhi Springer India 01.04.2020
Springer Nature B.V
Témata:
Algorithms
Constraint modelling
Datasets
Dynamic programming
Engineering
Engineering Economics
Logistics
Marketing
Optimization
Organization
Original Article
Particle swarm optimization
Performance evaluation
Quality Control
Reliability
Reservoir operation
Safety and Risk
Dynamic programming
Hybrid optimization
Reservoir operation
Genetic algorithm
Particle swarm optimization
ISSN:0975-6809, 0976-4348
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Abstract The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle Swarm Optimization (PSO). The reservoir operation problem is demonstrated in the form of a nonlinear optimization model subject to various constraints. Two case studies are considered. In the first case the efficiency of the proposed algorithm is tested on a small data set of 1 year and in the second case, data set taken is for 10 years. The results obtained are compared in terms of objective function value as well CPU time for performance evaluation of the integrated methods.
AbstractList The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle Swarm Optimization (PSO). The reservoir operation problem is demonstrated in the form of a nonlinear optimization model subject to various constraints. Two case studies are considered. In the first case the efficiency of the proposed algorithm is tested on a small data set of 1 year and in the second case, data set taken is for 10 years. The results obtained are compared in terms of objective function value as well CPU time for performance evaluation of the integrated methods.
The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle Swarm Optimization (PSO). The reservoir operation problem is demonstrated in the form of a nonlinear optimization model subject to various constraints. Two case studies are considered. In the first case the efficiency of the proposed algorithm is tested on a small data set of 1 year and in the second case, data set taken is for 10 years. The results obtained are compared in terms of objective function value as well CPU time for performance evaluation of the integrated methods.
Author Bilal
Pant, Millie
Rani, Deepti
Jain, S. K.
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Copyright The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2020
The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2020.
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Issue 2
Keywords Dynamic programming
Hybrid optimization
Reservoir operation
Genetic algorithm
Particle swarm optimization
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Snippet The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The...
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SubjectTerms Algorithms
Constraint modelling
Datasets
Dynamic programming
Engineering
Engineering Economics
Logistics
Marketing
Optimization
Organization
Original Article
Particle swarm optimization
Performance evaluation
Quality Control
Reliability
Reservoir operation
Safety and Risk
Title Dynamic programming integrated particle swarm optimization algorithm for reservoir operation
URI https://link.springer.com/article/10.1007/s13198-020-00974-z
https://www.proquest.com/docview/2400108843
Volume 11
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