Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm

Reddy, Janga M and Kumar, Nagesh D (2006) Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm. In: Water Resources Management, 20 (6). pp. 861-878.

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Abstract

This paper presents a Multi-objective Evolutionary Algorithm (MOEA) to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multiobjective 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 (MOOP), 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 is 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.

Item Type:	Journal Article
Publication:	Water Resources Management
Publisher:	Springer Netherlands
Additional Information:	Copyright of this article belongs to Springer Netherlands.
Keywords:	Multi-objective optimization;Genetic Algorithms;Reservoir operation;Pareto front;Irrigation;Hydropower
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	21 Dec 2006
Last Modified:	19 Sep 2010 04:32
URI:	http://eprints.iisc.ac.in/id/eprint/8989

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