Note on L#-convex Function Minimization Algorithms: Comparison of Murota's and Kolmogorov's Algorithms
Please always quote using this URN: urn:nbn:de:0297-zib-8979
- The concept of L##-convexity is introduced by Fujishige--Murota (2000) as a discrete convexity for functions defined over the integer lattice. The main aim of this note is to understand the difference of the two algorithms for L##-convex function minimization: Murota's steepest descent algorithm (2003) and Kolmogorov's primal algorithm (2005).
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| Author: | Akiyoshi Shioura |
|---|---|
| Document Type: | ZIB-Report |
| MSC-Classification: | 90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C27 Combinatorial optimization |
| Date of first Publication: | 2006/01/30 |
| Series (Serial Number): | ZIB-Report (06-03) |
| ZIB-Reportnumber: | 06-03 |
| Published in: | This paper is combined with another paper and the resulting paper is published as follows: Vladimir Kolmogorov and Akiyoshi Shioura: New Algorithms for Convex Cost Tension Problem with Application to Computer Vision. Discrete Optimization, 6 (4) (2009), 378-393 |
