A chaotic quantum bee colony optimization for thinned array

Design a new novel intelligence algorithm which is called as chaotic quantum bee colony optimization (CQBCO) for discrete optimization problem. The proposed CQBCO applies the chaotic theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. Then the proposed chaotic quantum bee colony algorithm is used to solve benchmark functions and optimization problem of thinned array. By hybridizing the quantum bee colony optimization and quantum computing theory, the quantum state and binary state of the bees can be well evolved by simulated quantum rotation gate and chaotic mechanical. The new thinned array method based on CQBCO can search the global optimal solution. Simulation results for thinned array are provided to show that the proposed thinned array method is superior to the thinned array methods based on other three intelligence algorithms.

[1]  Jong-Hwan Kim,et al.  Genetic quantum algorithm and its application to combinatorial optimization problem , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[2]  T. C. Cheston.  Phased array radar antenna , 1990 .

[3]  J. Galejs,et al.  Minimization of sidelobes in space tapered linear arrays , 1964 .

[4]  William H. Press,et al.  Numerical recipes , 1990 .

[5]  Y. T. Lo,et al.  Antenna Handbook: Theory, Applications, and Design , 1988 .

[6]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7]  Li-Pei Wong,et al.  Bee Colony Optimization algorithm with Big Valley landscape exploitation for Job Shop Scheduling problems , 2008, 2008 Winter Simulation Conference.

[8]  Vice President,et al.  9 IEEE ANTENNAS AND PROPAGATION SOCIETY , 1978 .