ArticleScientific reports2022
Travel time optimization on multi-AGV routing by reverse annealing.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- A smaller and more efficient one-hot encoding for QUBO.Scientific reports · 2026Article
- Micro-mobility dispatch optimization via quantum annealing incorporating historical data.Scientific reports · 2026Article
- Quantum annealing-based route optimization for commercial AGV operating systems in large-scale logistics warehouses.Scientific reports · 2025Article
- Optimization of connection patterns between mobile phones and base stations using quantum annealing.Scientific reports · 2025Article
- Enhancing multiple object tracking accuracy via quantum annealing.Scientific reports · 2025Article
- Routing and scheduling optimization for urban air mobility fleet management using quantum annealing.Scientific reports · 2025Article
- Article
- Hybrid quantum-classical computation for automatic guided vehicles scheduling.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Quantum annealing has been actively researched since D-Wave Systems produced the first commercial machine in 2011. Controlling a large fleet of automated guided vehicles is one of the real-world applications utilizing quantum annealing. In this study, we propose a formulation to control the traveling routes to minimize the travel time. We validate our formulation through simulation in a virtual plant and authenticate the effectiveness for faster distribution compared to a greedy algorithm that does not consider the overall detour distance. Furthermore, we utilize reverse annealing to maximize the advantage of the D-Wave's quantum annealer. Starting from relatively good solutions obtained by a fast greedy algorithm, reverse annealing searches for better solutions around them. Our reverse annealing method improves the performance compared to standard quantum annealing alone and performs up to 10 times faster than a commercial classical solver, Gurobi. This study extends a use of optimization with general problem solvers in the application of multi-AGV systems and reveals the potential of reverse annealing as an optimizer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.