Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/4796
Title: 116-Evolutionary Computing in Optimal Reservoir Operation.
Authors: Reddy, M. Janga
Kumar, D. Nagesh
Keywords: Reservoir Regulation
Decision Support System
Evolutionary Computing
Optimal Reservoir Operation
Genetic Algorithms (GA)
Ant Colony Optimization (ACO)
Particle Swarm Optimization (PSO)
Issue Date: 2009
Publisher: Allied Publishers Pvt. Limited, New Delhi
Abstract: Efficient design and operation of water resource systems is a challenging task in many real world applications. Many issues related to water resources require the solutions of optimization. As computers have become more powerful, the size and complexity of problems which can be simulated and solved by optimization techniques have correspondingly expanded. Real life water management problems involve nonlinear optimization and often associated with complexities of nonconvex objective functions and multimodal solutions. If the objective function is not known analytically, traditional methods are not applicable. Consequently these difficulties lead to go for non-conventional optimization techniques. Recently, evolutionary computation techniques have been receiving increased attention in view of their potential as global optimization techniques for complex problems. This popularity is mainly due to the robustness, ease of use and wide applicability of evolutionary algorithms. This paper aims to discuss some of the issues of evolutionary algorithms and summarizes applications of evolutionary computing techniques such as Genetic Algorithms (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) for effective water resources management, especially in the context of reservoir operation.
URI: http://117.252.14.250:8080/jspui/handle/123456789/4796
Appears in Collections:Proceedings of the International Conference on Water, Environment, Energy and Society (WEES-2009), 12-16 January 2009 at New Delhi, India, Vol.-2

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