Quantum-Enhanced Evolutionary Algorithms

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum-Enhanced Evolutionary Algorithms (QEAs) represent a novel approach to optimization, aiming to significantly accelerate the evolution of complex, high-dimensional evolutionary algorithms. This paper explores the potential of quantum mechanics to enhance the optimization process, focusing on leveraging quantum properties such as superposition and entanglement to accelerate exploration of the search space and improve convergence. We detail the core mechanism of QEAs, outlining the key design choices and theoretical underpinnings. The paper argues that the integration of quantum elements can provide a substantial performance advantage over classical approaches, particularly for problems exhibiting complex, high-dimensional landscapes. The research will demonstrate the efficacy of this approach through simulations and preliminary analysis, emphasizing the potential for enhanced search efficiency and robustness.

DOI: 10.5281/zenodo.22219688

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