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… Click to show full abstract
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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