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We present a comprehensive case study comparing the performance of D-Waves'quantum-classical hybrid framework, Fujitsu's quantum-inspired digitalannealer, and Gurobi's state-of-the-art classical solver in solving a transportrobot scheduling problem. This problem originates from an industrially relevantreal-world scenario. We provide three different models for our problemfollowing different design philosophies. In our benchmark, we focus on thesolution quality and end-to-end runtime of different model and solvercombinations. We find promising results for the digital annealer and someopportunities for the hybrid quantum annealer in direct comparison with Gurobi.Our study provides insights into the workflow for solving anapplication-oriented optimization problem with different strategies, and can beuseful for evaluating the strengths and weaknesses of different approaches.

An Optimization Case Study for solving a Transport Robot Scheduling Problem on Quantum-Hybrid and Quantum-Inspired Hardware