We present a polynomial time 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 as playing a fundamental role in tractable cases of discrete optimization. The algorithm is applicable also to a variant of quasi M-convex functions.
ASJC Scopus subject areas
- Applied Mathematics
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- Management Science and Operations Research
- Computer Graphics and Computer-Aided Design
- Computer Science(all)