标题： 量子退火在可扩展机器人装配线优化中的应用：案例研究 显示英文标题

标题： Application of quantum annealing for scalable robotic assembly line optimization: a case study

摘要： 在资源和工作站之间实现任务的均衡分配和优化是制造业中一个关键过程，旨在最大化效率、生产力和盈利能力，这被称为机器人装配线平衡（RALB）。 随着大规模定制所需的制造复杂性不断增加，传统的计算方法难以高效解决RALB问题。 为了解决这些可扩展性挑战，我们研究将量子计算，特别是量子退火，应用于基于现实世界的問題。 我们将整数规划公式转换为无约束二次二进制优化问题，然后使用混合量子经典算法在D-Wave Advantage 4.1量子计算机上求解。 在一项案例研究中，量子解决方案与精确解决方案进行了比较，展示了量子计算在提高制造生产力和降低成本方面的潜力。 然而，量子退火的局限性，包括硬件限制和特定问题的挑战，表明量子技术的持续进步将是提高其在RALB制造优化中适用性的必要条件。 显示英文摘要

摘要： The even distribution and optimization of tasks across resources and workstations is a critical process in manufacturing aimed at maximizing efficiency, productivity, and profitability, known as Robotic Assembly Line Balancing (RALB). With the increasing complexity of manufacturing required by mass customization, traditional computational approaches struggle to solve RALB problems efficiently. To address these scalability challenges, we investigate applying quantum computing, particularly quantum annealing, to the real-world based problem. We transform the integer programming formulation into a quadratic unconstrained binary optimization problem, which is then solved using a hybrid quantum-classical algorithm on the D-Wave Advantage 4.1 quantum computer. In a case study, the quantum solution is compared to an exact solution, demonstrating the potential for quantum computing to enhance manufacturing productivity and reduce costs. Nevertheless, limitations of quantum annealing, including hardware constraints and problem-specific challenges, suggest that continued advancements in quantum technology will be necessary to improve its applicability to RALB manufacturing optimization.