Reverse Convex Programming Approach in the Space of Extreme Criteria for Optimization over Efficient Sets
The problem of minimizing a convex function over the difference of two convex sets is called ‘reverse convex program’. This is a typical problem in global optimization, in which local optima are in general different from global optima. Another typical example in global optimization is the optimizati...
Saved in:
| Published in: | Journal of optimization theory and applications Vol. 147; no. 2; pp. 263 - 277 |
|---|---|
| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
Boston
Springer US
01.11.2010
Springer |
| Subjects: | |
| ISSN: | 0022-3239, 1573-2878 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The problem of minimizing a convex function over the difference of two convex sets is called ‘reverse convex program’. This is a typical problem in global optimization, in which local optima are in general different from global optima. Another typical example in global optimization is the optimization problem over the efficient set of a multiple criteria programming problem. In this article, we investigate some special cases of optimization problems over the efficient set, which can be transformed equivalently into reverse convex programs in the space of so-called extreme criteria of multiple criteria programming problems under consideration. A suitable algorithm of branch and bound type is then established for globally solving resulting problems. Preliminary computational results with the proposed algorithm are reported. |
|---|---|
| ISSN: | 0022-3239 1573-2878 |
| DOI: | 10.1007/s10957-010-9721-2 |