Quantum Obfuscated Optimization Algorithm Dynamic Adjustment (QOADA)

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Obfuscated Optimization Algorithm Dynamic Adjustment (QOADA) is a novel optimization algorithm designed to enhance the stability of iterative optimization processes by dynamically adjusting optimization parameters based on observed noise and uncertainty within the optimization landscape. This approach leverages the unique properties of quantum-mechanical optimization algorithms to achieve a more robust and adaptive optimization strategy. The core mechanism involves a continuous, real-time assessment of the optimization process, triggering adjustments to key parameters based on these assessments. This dynamic adaptation mitigates the effects of noise and uncertainty, leading to improved convergence rates and a more reliable outcome. The paper details the theoretical framework, implementation steps, and experimental results demonstrating the effectiveness of QOADA in various optimization scenarios.

DOI: 10.5281/zenodo.22187945

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