A hybrid chaotic genetic algorithm for short-term hydro system scheduling

Authors:
Xiaohui Yuan;Yanbin Yuan;Yongchuan Zhang
Affiliations:
Department of Hydropower and Automation Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China;Department of Hydropower and Automation Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China;Department of Hydropower and Automation Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
Venue:
Mathematics and Computers in Simulation
Year:
2002

Citing 1
Cited 8

A new mutation rule for evolutionary programming motivated frombackpropagation learning

IEEE Transactions on Evolutionary Computation

Optimal matching by the transiently chaotic neural network

Applied Soft Computing
Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Mathematics and Computers in Simulation
Chaos Cultural Particle Swarm Optimization and Its Application

ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
The hybrid forecasting model based on chaotic mapping, genetic algorithm and support vector machine

Expert Systems with Applications: An International Journal
Short-term combined economic emission hydrothermal scheduling using improved quantum-behaved particle swarm optimization

Expert Systems with Applications: An International Journal
Chaos-based improved immune algorithm (CBIIA) for resource-constrained project scheduling problems

Expert Systems with Applications: An International Journal
Design optimization with chaos embedded great deluge algorithm

Applied Soft Computing
SVR with chaotic genetic algorithm in taiwanese 3g phone demand forecasting

SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a novel hybrid chaotic genetic algorithm (HCGA) to solve the short-term generation scheduling of hydro system. The integration of chaotic sequence and genetic algorithm with a new self-adaptive error back-propagation mutation operator are developed, which can overcome premature and increase the convergence speed. Simulation results have demonstrated that the proposed approach is feasible and effective for the applications.