Algorithm for Dynamic Multi-Objective Distributed Constraint Optimization
| Project/Area Number |
26330268
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Kobe University |
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Principal Investigator |
Okimoto Tenda 神戸大学, 海事科学研究科, 准教授 (10632432)
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| Co-Investigator(Renkei-kenkyūsha) |
Inoue Katsumi 国立情報学研究所, 情報学プリンシプル研究系, 教授 (10252321)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 分散制約最適化 / 多目的分散制約最適化 / パレート最適性 / 多目的制約最適化問題 / 時間割作成問題 / ナーススケジューリング問題 / 分散制約最適化問題 / パレート最適解 / チーム編成問題 / 多目的分散制約最適化問題 |
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| Outline of Final Research Achievements |
In this research, the framework of a dynamic multi-objective distributed constraint optimization problem has been investigated. First, several efficient algorithms have been developed for solving a multi-objective distributed constraint optimization problem, namely (i) a complete algorithm which can guarantee to find all Pareto optimal solutions (called Pareto front), (ii) an incomplete algorithm that finds a subset of Pareto front, i.e., the obtained solutions can guarantee Pareto optimality, and (iii) an approximation algorithm. Next, a formal framework for a dynamic multi-objective distributed constraint optimization problem is defined and an efficient algorithm is also proposed. Finally, as an application domain, we apply our results to a team formation problem and a nurse-scheduling problem. In summary, this research can be executed according to the research plan described in my proposal. Also, several articles about this research have been accepted in the top conferences for AI.
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Report
(4 results)
Research Products
(48 results)
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[Journal Article] Multi-objective Nurse Rerostering Problem2016
Author(s)
Shih-Min Wu, Tenda Okimoto, Katsutoshi Hirayama, Katsumi Inoue
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Journal Title
Multi-agent and Complex Systems, Studies in Computational Intelligence
Volume: 607
Pages: 139-152
DOI
ISBN
9789811025631, 9789811025648
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] Leximin Asymmetric Multiple Objective DCOP on Factor Graph2015
Author(s)
Toshihiro Matsui, Marius Silaghi, Tenda Okimoto, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo
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Journal Title
In proceedings of the 18th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2015)
Pages: 134-151
DOI
ISBN
9783319255231, 9783319255248
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] How to Form a Task-Oriented Robust Team2015
Author(s)
Tenda Okimoto, Nicolas Schwind, Maxime Clement, Tony Ribeiro, Katsumi Inoue, Pierre Marquis
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Journal Title
In proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015)
Pages: 395-403
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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