Abstract
We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are nonlinear discrete functions with (poly)matroid structures, which are being recognized to play a fundamental role in tractable cases of discrete optimization. The novel idea of the algorithm is to use an individual scaling factor for each coordinate.
Original language | English |
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Pages (from-to) | 21-35 |
Number of pages | 15 |
Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 2337 LNCS |
Publication status | Published - 2002 Dec 1 |
Externally published | Yes |
Event | 9th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2002 - Cambridge, MA, United States Duration: 2002 May 27 → 2002 May 29 |
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)