Optimal reservoir operation using multi-objective evolutionary algorithm

Optimal reservoir operation using multi-objective evolutionary algorithm

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Article ID: iaor20071986
Country: Netherlands
Volume: 20
Issue: 6
Start Page Number: 861
End Page Number: 878
Publication Date: Dec 2006
Journal: Water Resources Management
Authors: ,
Keywords: heuristics: genetic algorithms, developing countries
Abstract:

This paper presents a Multi-objective Evolutionary Algorithm to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multi-objective optimization is to find a set of well distributed optimal solutions along the Pareto front. Classical optimization methods often fail in attaining a good Pareto front. To overcome the drawbacks faced by the classical methods for Multi-objective Optimization Problems, this study employs a population based search evolutionary algorithm namely Multi-objective Genetic Algorithm (MOGA) to generate a Pareto optimal set. The MOGA approach is applied to a realistic reservoir system, namely Bhadra Reservoir system, in India. The reservoir serves multiple purposes: irrigation, hydropower generation and downstream water quality requirements. The results obtained using the proposed evolutionary algorithm are able to offer many alternative policies for the reservoir operator, giving flexibility to choose the best out of them. This study demonstrates the usefulness of MOGA for a real life multi-objective optimization problem.

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