Improving the Performance of the Optimization Technique Using Chaotic Algorithm

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

Optimizing the operations of a multi-reservoir systems are complex because of their larger dimension and convexity of the problem. The advancement of soft computing techniques not only overcomes the drawbacks of conventional techniques but also solves the complex problems in a simple manner. However, if the problem is too complex with hardbound variables, the simple evolutionary algorithm results in slower convergence and sub-optimal solutions. In evolutionary algorithms, the search for global optimum starts from the randomly generated initial population. Thus, initializing the algorithm with a better initial population not only results in faster convergence but also results in global optimal solution. Hence in the present study, chaotic algorithm is used to generate the initial population and coupled with genetic algorithm (GA) to optimize the hydropower production from a multi-reservoir system in India. On comparing the results with simple GA, it is found that the chaotic genetic algorithm (CGA) has produced slightly more hydropower than simple GA in fewer generations and also converged quickly.

Keywords

Optimization Genetic algorithm Chaotic algorithm  Multi-hydropower system. 

Notes

Acknowledgments

The authors gratefully acknowledge the Ministry of Water Resources, Government of India, New Delhi, for sponsoring this research project. The authors also thank Chief Engineer, KHEP, Executive Engineer, Koyna Dam and Executive Engineer, Kolkewadi Dam for providing the necessary data.

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Civil EngineeringIndian Institute of Technology BombayMumbaiIndia

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