Polynomial-time Algorithms for Analysis and Control of Epidemic Spreading Processes

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K13777
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 21040:Control and system engineering-related
• Research Institution: Osaka University (2019-2020); Nara Institute of Science and Technology (2018)
• Principal Investigator: Ogura Masaki 大阪大学, 情報科学研究科, 准教授 (10800732)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: 複雑ネットワーク / 制御理論 / 最適化 / 制御工学 / 非負システム / 設計工学 / 確率過程

Outline of Final Research Achievements

We have established novel frameworks for the analysis and synthesis of various classes of networked dynamics. For the epidemic processes over networks, we have obtained analysis tools based on non-backtracking matrices and higher-order moments. For positive dynamical systems, we have constructed a synthesis theory based on geometric programming, which is then applied for the optimal design of product development processes.

Free Research Field

複雑ネットワーク

Academic Significance and Societal Importance of the Research Achievements

多数のシステムが複雑に結合するネットワークダイナミクスは，感染症伝搬や情報伝播など様々な状況に現れる．ネットワークが大規模な場合，このようなダイナミクスの解析や制御に従来の手法をそのまま用いることは，数値的に効率が必ずしも良いとは限らない．そこで本研究ではこの困難を克服するために，様々な数理に性能が裏打ちされた，数値的に効率の良いネットワーク解析・制御手法を確立した．