Quantum-Enhanced Metamorphic Optimization

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper investigates the application of quantum computing to enhance metamorphic optimization, a challenging problem for complex optimization. We propose a novel quantum-enhanced metamorphic optimization technique predicated on leveraging quantum properties to accelerate the optimization process and improve robustness. Traditional optimization methods often struggle with the complexity of these problems, necessitating computationally intensive approaches. This work explores the potential of quantum computing to address these limitations, aiming to achieve substantial improvements in optimization speed and solution quality. We detail the core mechanism, the rationale behind the quantum enhancement, and the expected results through analysis and simulation. The core claim of this study is that implementing a quantum-enhanced metamorphic optimization technique results in improved robustness and accelerated convergence.

DOI: 10.5281/zenodo.22219750

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