Comparative analysis of Simulated Annealing, Simulated Quenching and Genetic Algorithms for optimal reservoir operation

Authors:
A. Vasan;Komaragiri Srinivasa Raju
Affiliations:
Department of Civil and Environmental Engineering, The University of Western Ontario, London, Ontario, Canada N6A 5B9;Civil Engineering Group, Birla Institute of Technology and Science, Pilani, Rajasthan 333 031, India
Venue:
Applied Soft Computing
Year:
2009

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Abstract

The present study deals with the application of non-traditional optimization techniques, namely, Simulated Annealing (SA), Simulated Quenching (SQ) and Real-coded Genetic Algorithms (RGA) to a case study of Mahi Bajaj Sagar Project, India. The objective of the study is to maximize the annual net benefits subjected to various irrigation planning constraints for 75% dependable flow scenario. Extensive sensitivity analysis on various parameters used in above techniques indicated that they yielded same solution corresponding to a set of optimal combination of parameters. It is concluded that SA, SQ and RGA can be utilized for efficient planning of any irrigation system with suitable modifications.