102. Improved branch-and-bound for integer D-Optimality
Invited abstract in session TB-7: Global optimization I, stream Global optimization.
Thursday, 10:05 - 11:20Room: M:I
Authors (first author is the speaker)
| 1. | Jon Lee
|
| Industrial and Operations Engineering Department, University of Michigan |
Abstract
We develop a branch-and-bound algorithm for the integer D-optimality problem, a central problem in statistical design theory, based on two convex relaxations, employing variable-bound tightening and fast local-search procedures, testing our ideas on randomly-generated test problems. We are able to prove some relationships between various bounds for the related data-fusion problem.
Keywords
- Global optimization
- Convex and non-smooth optimization
- Mixed integer nonlinear optimization
Status: accepted
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