Quantum mapping algorithm for structural non-probabilistic reliability optimization

The continuous development of advanced aircraft structures brings complex service environments and multi-variable/multi-reliability constraints design scenarios. This also increases the need for refined, lightweight, and highly reliable designs. Traditional optimization methods for structural design often consume significant computational resources, which compromises the optimization's effectiveness and efficiency. Quantum computing with its powerful computational capabilities and inherent parallelism shows great promise in handling multi-variable and multi-reliability constraints problems. This paper presents a quantum mapping algorithm for non-probabilistic reliability optimization (QMA-NPRO) to address structural optimization. The method employs a hybrid quantum–classical algorithm framework, using quantum states to represent reliability constraints and guide the evolutionary process, eliminating the need for penalty functions in constraint handling, thus improving computational efficiency and solution quality. This work extends quantum computing applications to structural reliability and proposes a feasible design framework for addressing multi-variable/multi-reliability constraints problems in aerospace structural design.