Mathematical programming approaches to robust optimization problems
| Project/Area Number |
24650004
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Fundamental theory of informatics
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| Research Institution | Nagoya University |
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Principal Investigator |
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| Research Collaborator |
WU Wei 名古屋大学, 大学院情報科学研究科, 博士課程後期課程
MARTELLO Silvano University of Bologna, Professor
IORI Manuel University of Modena and Reggio Emilia, Associate Professor
FURINI Fabio Université Paris Dauphine, Assistant Professor
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| Project Period (FY) |
2012-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 組合せ最適化 / ロバスト最適化 / 厳密解法 / 発見的解法 / 発見的手法 |
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| Outline of Final Research Achievements |
Many real-world problems can be formulated as combinatorial optimization problems. Although most of them are know to be NP-hard, there exist many algorithms that obtain good quality solutions in reasonable computation time. However, most of such optimization methods are based on the assumption that input data are known a priori and are fixed. On the other hand, input data are often ambiguous and uncertain. We developed several exact and heuristic algorithms to obtain solutions that are robust to such uncertainty, for a representative combinatorial optimization problem called the 0-1 knapsack problem, and we confirmed that the proposed algorithms output good solutions in reasonable computation time.
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Report
(5 results)
Research Products
(11 results)
