Volume 7 Number 1
February 2010
Article Contents
Han Xue, Xun Li and Hong-Xu Ma. Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis. International Journal of Automation and Computing, vol. 7, no. 1, pp. 115-122, 2010. doi: 10.1007/s11633-010-0115-6
Cite as: Han Xue, Xun Li and Hong-Xu Ma. Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis. International Journal of Automation and Computing, vol. 7, no. 1, pp. 115-122, 2010. doi: 10.1007/s11633-010-0115-6

Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis

Author Biography:
  • Corresponding author: Han Xue received the M.Sc.degree from National University of Defense Technology,PRC in 2007.
  • Received: 2008-11-27
Fund Project:

supported by National High Technology Research and Development Program of China (863 Program) (No.2007AA041603);National Natural Science Foundation of China (No.60475035);Key Technologies Research and Development Program Foundation of Hunan Province of China (No.2007FJ1806);Science and Technology Research Plan of National University of Defense Technology (No.CX07-03-01);Top Class Graduate Student Innovation Sustentation Fund of National University of Defense Technology (No.B070302.)

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Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis

    Corresponding author: Han Xue received the M.Sc.degree from National University of Defense Technology,PRC in 2007.
Fund Project:

supported by National High Technology Research and Development Program of China (863 Program) (No.2007AA041603);National Natural Science Foundation of China (No.60475035);Key Technologies Research and Development Program Foundation of Hunan Province of China (No.2007FJ1806);Science and Technology Research Plan of National University of Defense Technology (No.CX07-03-01);Top Class Graduate Student Innovation Sustentation Fund of National University of Defense Technology (No.B070302.)

Abstract: This paper proposes an adaptive chaos quantum honey bee algorithm (CQHBA) for solving chance-constrained programming in random fuzzy environment based on random fuzzy simulations. Random fuzzy simulation is designed to estimate the chance of a random fuzzy event and the optimistic value to a random fuzzy variable. In CQHBA, each bee carries a group of quantum bits representing a solution. Chaos optimization searches space around the selected best-so-far food source. In the marriage process, random interferential discrete quantum crossover is done between selected drones and the queen. Gaussian quantum mutation is used to keep the diversity of whole population. New methods of computing quantum rotation angles are designed based on grads. A proof of convergence for CQHBA is developed and a theoretical analysis of the computational overhead for the algorithm is presented. Numerical examples are presented to demonstrate its superiority in robustness and stability, efficiency of computational complexity, success rate, and accuracy of solution quality. CQHBA is manifested to be highly robust under various conditions and capable of handling most random fuzzy programmings with any parameter settings, variable initializations, system tolerance and confidence level, perturbations, and noises.

Han Xue, Xun Li and Hong-Xu Ma. Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis. International Journal of Automation and Computing, vol. 7, no. 1, pp. 115-122, 2010. doi: 10.1007/s11633-010-0115-6
Citation: Han Xue, Xun Li and Hong-Xu Ma. Random Fuzzy Chance-constrained Programming Based on Adaptive Chaos Quantum Honey Bee Algorithm and Robustness Analysis. International Journal of Automation and Computing, vol. 7, no. 1, pp. 115-122, 2010. doi: 10.1007/s11633-010-0115-6
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