For optimzing complex functions with high-dimension, a real-coded quantum evolutionary algorithm (RCQEA) is proposed on the basis of the concept and principles of quantum computing such as qubits and superposition of ...
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ISBN:
(纸本)9781424408276
For optimzing complex functions with high-dimension, a real-coded quantum evolutionary algorithm (RCQEA) is proposed on the basis of the concept and principles of quantum computing such as qubits and superposition of states. Firstly, in this algorithm, real-coded triploid chromosomes, whose alleles are composed of real variable and a pair of probability amplitudes of the correspinding states of one qubit, are constructed to keep the diversity of solution. Secondly, complementary double mutation operator (CDMO), which is designed according to a pair of probability amplitudes of the correspinding states of one qubit satisfying the normalization condition, as well as quantum rotation gate (QRG) are used to update chromosomes, which can treat the balance between exploration and exploitation. Thirdly, discrete crossover (DC) is employed to expand search space. Finally, "Hill-climbing" selection (HCS) is adopted to accelerate the convergence speed. Simulation results on 4 benchmark complex functions with high-dimension show that RCQEA is not only effective, efficient, but also very adaptive to the dimensions, and has the characteristics of rapider convergence, more powerful global search capability and better stability.
Whether wireless sensor network covers the target field availably is measured by the network cover rate and the node redundancy rate. To solve this multi-objective optimization problem, multi-objective quantum cultura...
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ISBN:
(纸本)9783642412783;9783642412776
Whether wireless sensor network covers the target field availably is measured by the network cover rate and the node redundancy rate. To solve this multi-objective optimization problem, multi-objective quantum cultural algorithm is proposed. It effectively utilizes the implicit knowledge extracted from the non-domination individuals to promote more efficient search. Two highlights include: 1. The rectangle's height of each allele is calculated in accordant with the non-dominated sort among individuals. 2. The update operation of quantum individuals and the mutation operator are directed by the implicit knowledge. Taken a typical wireless sensor network with 25 sensor nodes as an example, simulation results indicate that the layout of wireless sensor network obtained by the proposed algorithm have larger network cover rate and lower node redundancy rate.
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