Dynamic programming integrated particle swarm optimization algorithm for reservoir operation

• Published in: International journal of system assurance engineering and management Vol. 11; no. 2; pp. 515 - 529
• Main Authors: Bilal, Rani, Deepti, Pant, Millie, Jain, S. K.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.04.2020; Springer Nature B.V
• Subjects: 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
• DOI: 10.1007/s13198-020-00974-z

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.