| Project/Area Number |
12680459
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
社会システム工学
|
|---|
| Research Institution | The Institute of Statistical Mathematics |
|---|
Principal Investigator |
ITO Satoshi The Institute of Statistical Mathematics, Theory and numerical methods of generalized semi-infinite programming, Associate Professor, 統計計算開発センター, 助教授 (50232442)
|
|---|
| Project Period (FY) |
2000 – 2003
|
| Project Status |
Completed (Fiscal Year 2003)
|
| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2003: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2002: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2001: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2000: ¥900,000 (Direct Cost: ¥900,000)
|
|---|
| Keywords | semi-infinite programming / min-max programming / nonlinear programming / convex programming / nondifferentiable optimization / infinite programming / optimal filter design / global optimization / 無限ゲーム / min-max問題 / 線形計画 / 2次計画 / 非線型計画 / 最適制御 |
|---|
| Research Abstract |
The purpose of this research project is to develop efficient numerical methods, with a software package, for generalized semi-infinite programming (SIP). Numerical methods developed in this project include (1) an algorithm based on duality theory for solving convex SIP problems, (2) an algorithm based on local reduction within a framework of sequential quadratic programming for solving nonlinear SIP problems, (3) an algorithm based on nondifferentiable optimization theory for solving nonlinear SIP problems. We have also implemented (4) an approximation algorithm based on cutting plane strategy and (5) a two-phase algorithm based on cutting plane and local reduction. Also as further research directions, we have investigated (6) a path-following algorithm. based on continuous descent methods, together with related stiff systems of ordinary differential equations, and (7) numerical methods based on semi definite programming relaxations. Some of these numerical algorithms have been implemented and applied to problems of optimal filter design, global optimization, min-max programming, infinite games and optimal control, and these are now being compiled into a software package written in the Matlab environment, which will soon become available through our web site.
|
