We present a comprehensive case study comparing the performance of D-Waves' quantum-classical hybrid framework, Fujitsu's quantum-inspired digital annealer, and Gurobi's state-of-the-art classical solver in solving a transport robot scheduling problem. This problem originates from an industrially relevant real-world scenario. We provide three different models for our problem following different design philosophies. In our benchmark, we focus on the solution quality and end-to-end runtime of different model and solver combinations. We find promising results for the digital annealer and some opportunities for the hybrid quantum annealer in direct comparison with Gurobi. Our study provides insights into the workflow for solving an application-oriented optimization problem with different strategies, and can be useful for evaluating the strengths and weaknesses of different approaches.

翻译：我们提出了一项综合性案例研究，对比了D-Wave的量子-经典混合框架、富士通的量子启发式数字退火器以及Gurobi的最先进经典求解器在解决运输机器人调度问题时的性能表现。该问题源于工业相关的实际场景。我们遵循不同设计理念，为问题提供了三种不同模型。在基准测试中，我们重点关注不同模型与求解器组合的求解质量及端到端运行时间。通过与Gurobi的直接比较，我们发现数字退火器展现出有前景的结果，而混合量子退火器也呈现若干潜在优势。本研究为采用不同策略解决应用导向的优化问题提供了工作流洞察，有助于评估不同方法的优劣。