Hybrid global optimization method
A technology for global optimization and optimization problems, applied in the field of optimization, can solve problems such as difficult to jump out of local optimum, and achieve the effect of accelerating search and improving search efficiency
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[0122] In order to verify the effectiveness of the hybrid global optimization algorithm, the three classical functions were optimized 30 times using chaotic particle swarm, sequence quadratic programming and hybrid global optimization algorithms, and the optimal values of the functions obtained were compared, and the calculation of the algorithm was analyzed. The size of the precision.
[0123] The algorithm parameters are set as: learning factor c 1 = c 2 =1.49, the number of particles N=40, the maximum number of iterations of particle swarm optimization MaxDT=100, the range of the flying speed allowed by the particles is [v min v max ]=[-10 10], the maximum number of iterations of chaotic search M=100, the adjustment parameter of chaotic search β=0.1, where the critical value of fitness variance [σ 2 ] and then set it according to the specific situation. The information of the three benchmark functions is shown in Table 1:
[0124] Table 1
[0125]
[0126] Three...
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