A hybrid quantum-based PIO algorithm for global numerical optimization

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作者
Boyi Chen
Hao Lei
Haidong Shen
Yanbin Liu
Yuping Lu
机构
[1] Nanjing University of Aeronautics and Astronautics,College of Astronautics
[2] Nanjing University of Aeronautics and Astronautics,College of Automation Engineering
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PIO; global convergence; numerical optimization; QEA;
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摘要
A novel hybrid quantum-based pigeon-inspired optimization (PIO) algorithm for global numerical optimization is proposed to perceive deceptiveness and preserve diversity. In the proposed algorithm, the current best solution is regarded as a linear superposition of two probabilistic states, namely positive and deceptive. Through a quantum rotation gate, the positive probability is either enhanced or reset to balance exploration and exploitation. Simulation results reveal that the hybrid quantum-based PIO algorithm demonstrates an outstanding performance in global optimization owing to preserving diversity in the early evolution. As a result, the stability of the algorithm is enhanced so that the precision of optimization is improved statistically. The proposed algorithm is demonstrated to be effective for solving multimodal and non-convex problems in higher dimension with a smaller population size.
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