Reservoir Flood Control Operation Based on Adaptive Immune Differential Evolution Algorithm

2017 2nd Asia Conference on Power and Electrical Engineering

能源学;电工学

Zou, Qiang^1 ; Lu, Jun^1 ; Yu, Shan^1

Changjiang Institute of Survey, Planning, Design and Research, Wuhan

430010, China^1

关键词: Complex problems;    Crossover factor;    Differential evolution algorithms;    Fast convergence;    Flood control operations;    Immune clonal selections;    Multi-constraints;    Optimal solutions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/199/1/012033/pdf
DOI  :  10.1088/1757-899X/199/1/012033

来源: IOP

【 摘 要 】

Reservoir flood control operation (RFCO) is a high dimensional complex problem with multi-stages, multi-variables and multi-constraints, and its optimal solution is not easy to get. Differential evolution algorithm (DE) can be applied in RFCO, but its species diversity may sharply decline at the last evolution and lead into local optimal. Therefore, based on the adaptively controlling for mutation factor and crossover factor in each generation and immune clonal selection for better individuals, then adaptive immune differential evolution algorithm (AIDE) was proposed. And test function simulation verified the feasibility and efficiency of AIDE. Finally, AIDE was employed for RFCO and case study showed that AIDE could get better flood control benefit with fast convergence and high accuracy, moreover the outcomes of this research provided an effective way for RFCO.