Abstract
We present a polynomial time domain scaling algorithm for the minimization of an M-convex function. M-convex functions are non-linear 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.
This work is supported by a Grant-in-Aid of the Ministry of Education, Culture, Sports, Science and Technology of Japan.
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Tamura, A. (2002). A Coordinatewise Domain Scaling Algorithm for M-convex Function Minimization. In: Cook, W.J., Schulz, A.S. (eds) Integer Programming and Combinatorial Optimization. IPCO 2002. Lecture Notes in Computer Science, vol 2337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47867-1_3
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DOI: https://doi.org/10.1007/3-540-47867-1_3
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