192 research outputs found

    On Equivalence of Mâ™®^\natural-concavity of a Set Function and Submodularity of Its Conjugate

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    A fundamental theorem in discrete convex analysis states that a set function is Mâ™®^\natural-concave if and only if its conjugate function is submodular. This paper gives a new proof to this fact

    Fundamentals in Discrete Convex Analysis

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    This talk describes fundamental properties of M-convex and L-convex functions that play the central roles in discrete convex analysis. These concepts were originally introduced in combinatorial optimization, but turned out to be relevant in economics. Emphasis is put on discrete duality and conjugacy respect to the Legendre-Fenchel transformation. Monograph information: http://www.misojiro.t.u-tokyo.ac.jp/~murota/mybooks.html#DCAsiam200

    Discrete Midpoint Convexity

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    For a function defined on a convex set in a Euclidean space, midpoint convexity is the property requiring that the value of the function at the midpoint of any line segment is not greater than the average of its values at the endpoints of the line segment. Midpoint convexity is a well-known characterization of ordinary convexity under very mild assumptions. For a function defined on the integer lattice, we consider the analogous notion of discrete midpoint convexity, a discrete version of midpoint convexity where the value of the function at the (possibly noninteger) midpoint is replaced by the average of the function values at the integer round-up and round-down of the midpoint. It is known that discrete midpoint convexity on all line segments with integer endpoints characterizes L♮^{\natural}-convexity, and that it characterizes submodularity if we restrict the endpoints of the line segments to be at ℓ∞\ell_\infty-distance one. By considering discrete midpoint convexity for all pairs at ℓ∞\ell_\infty-distance equal to two or not smaller than two, we identify new classes of discrete convex functions, called local and global discrete midpoint convex functions, which are strictly between the classes of L♮^{\natural}-convex and integrally convex functions, and are shown to be stable under scaling and addition. Furthermore, a proximity theorem, with the same small proximity bound as that for L♮^{\natural}-convex functions, is established for discrete midpoint convex functions. Relevant examples of classes of local and global discrete midpoint convex functions are provided.Comment: 39 pages, 6 figures, to appear in Mathematics of Operations Researc

    Note on Minimization of Quasi Mâ™®^\natural-convex Functions

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    For a class of discrete quasi convex functions called semi-strictly quasi Mâ™®^\natural-convex functions, we investigate fundamental issues relating to minimization, such as optimality condition by local optimality, minimizer cut property, geodesic property, and proximity property. Emphasis is put on comparisons with (usual) Mâ™®^\natural-convex functions. The same optimality condition and a weaker form of the minimizer cut property hold for semi-strictly quasi Mâ™®^\natural-convex functions, while geodesic property and proximity property fail
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