2021 Fiscal Year Research-status Report
Applications of Large-scale Real-world Geospatial Optimization Problems Using Ising Machines
| Project/Area Number |
21K17747
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| Research Institution | Waseda University |
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Principal Investigator |
鮑 思雅 早稲田大学, 理工学術院, 講師(任期付) (60875425)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | 地理情報処理 / イジング計算機 / 組み合わせ問題 |
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| Outline of Annual Research Achievements |
Applications of geospatial optimization problems have been of great interest for decades in fields of science and industry. Large-scale optimization problems are difficult to solve with conventional computers. Fortunately, Ising machines have been developed to tackle these problems by mapping the optimization problem onto the Ising models. However, current applications of Ising machines are focusing on non-real-world (sample) problems, and meanwhile, due to the spin limitation, Ising
models for large-scale real-world problems cannot be directly embedded onto the current Ising machines.
In the year of 2021, this research focus on the problem of multiday travel problem and has successfully mapped the problem onto Ising models and evaluated the proposed method by real Ising machine. High-quality travel plans can be achieved with none constraint violation according to the results from experiments in Sapporo area.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The research process is running smoothly in accordance with the proposed research plan.
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| Strategy for Future Research Activity |
As mentioned above, the most important point is how to smoothly and efficiently transfer the key elements into Ising models for large-scale problems.
In the next fiscal year, large-scale experiments will be conducted for performance evaluations. Meanwhile, methods for effective spin reduction will be investigated.
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