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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This work was supported by National Natural Science Foundation of China (Grant Nos. 61403191, 11572149), Funding of Jiangsu Innovation Program for Graduate Education (Grant Nos. KYLX 0281, KYLX15 0318, NZ2015205), and Fundamental Research Funds for the Central Universities, Aerospace Science and Technology Innovation Fund (CASC).
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Chen, B., Lei, H., Shen, H. et al. A hybrid quantum-based PIO algorithm for global numerical optimization. Sci. China Inf. Sci. 62, 70203 (2019). https://doi.org/10.1007/s11432-018-9546-4
- global convergence
- numerical optimization