一个优化案例研究解决运输机器人调度问题在量子混合和量子启发的硬件.
Dominik Leib1, Tobias Seidel2, Sven Jäger2
1Fraunhofer ITWM, Optimization Department, 67663, Kaiserslautern, Germany. dominik.leib@itwm.fraunhofer.de.
Scientific reports
|November 1, 2023
概括
我们比较了用于运输机器人调度问题的量子和经典解决方法. 富士通是一家富士通公司.
科学领域:
- 计算优化计算优化
- 量子计算应用 量子计算应用
- 运营研究 运营研究
背景情况:
- 工业运输机器人调度带来了复杂的优化挑战.
- 评估新兴的量子和量子启发的计算对于实际问题至关重要.
- 经典的解决方案仍然是优化任务的基准.
研究的目的:
- 为了对D-Wave的混合量子-经典框架,富士通的数字化器和古罗比的经典解决器进行比较.
- 在解决方案质量和运行时间方面评估性能,用于现实世界运输机器人调度问题.
- 为了比较优化任务的三个不同的建模方法.
主要方法:
- 为运输机器人调度问题开发三种数学模型.
- 解决方案的实施和执行:D-Wave的混合框架,富士通的数字化器和古罗比的经典解决方案.
- 以解决方案质量和端到端执行时间为重点的比较分析.
主要成果:
- 量子启发的数字化器表现出有前途的性能.
- 混合量子炉显示出潜力,并确定了特定的机会.
- 直接比较突出了与最先进的经典解决方案相比,每个方法的优缺点.
结论:
- 这项研究为应用不同的优化策略来解决现实世界问题提供了宝贵的见解.
- 发现有助于评估量子,量子启发和经典计算范式的实际适用性和性能.
- 这项研究提供了一种工作流程,以应对面向应用的优化挑战.
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