| Project/Area Number |
14580389
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
計算機科学
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| Research Institution | Chuo University |
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Principal Investigator |
ASANO Takao Chuo University, Faculty of Science and Engineering, Professor, 理工学部, 教授 (90124544)
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| Co-Investigator(Kenkyū-buntansha) |
ASANO Yasuhito Tohoku University, Graduate School of Information Sceince, Research Associate, 大学院・情報科学研究科, 助手 (20361157)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2004: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2002: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | Approximation Algorithms / Network Algorithms / NP-hard / Linear Programming / Semi-definite Programming |
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| Research Abstract |
The objective of this research is to investigate a systematic approach to network approximation algorithms with performance guarantees from both theoretical and practical points of veiw and to clarify its usefulness and bound on the development of algorithmic researches which will be important for information technology in this centuary. To achive this objective, we have done the following researches.
We made an investigation on semi-definite programming and linear programming techniques, which are considerd to be potential systematic approaches to designing and analyzing network approximation algorithms with performance guarantees.
More specifically, we surveyed the recent trends by translating the book of Approximation Algorithms written by V.V.Vazirani and the book of Combinatorial Optimization written by B.Korte and J.Vygen. These two books are considered to be the best books describing the most recent progress in network algorithms and approximation algorithms in the world.
Through this survey, we obtained some power and applied this power to developing new network approximation algorithms.
Acutually, we proposed the current best approximation algorithm for MAX SAT.
We also proposed several algorithms for exploiting inforamtion from the Web based on network approximation algorithms.
These proposed algorithms were published in high standard international conferences and Journal.
In view of this, we believe, the objective of this research is satisfactorily achieved.
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