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  2. K-convex function - Wikipedia

    en.wikipedia.org/wiki/K-convex_function

    The policy is characterized by two numbers s and S, , such that when the inventory level falls below level s, an order is issued for a quantity that brings the inventory up to level S, and nothing is ordered otherwise. Gallego and Sethi [2] have generalized the concept of K-convexity to higher dimensional Euclidean spaces.

  3. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    Modeling tools are separate pieces of software that let the user specify an optimization in higher-level syntax. They manage all transformations to and from the user's high-level model and the solver's input/output format. The table below shows a mix of modeling tools (such as CVXPY and Convex.jl) and solvers (such as CVXOPT and MOSEK).

  4. Convex analysis - Wikipedia

    en.wikipedia.org/wiki/Convex_analysis

    then is called strictly convex. [1]Convex functions are related to convex sets. Specifically, the function is convex if and only if its epigraph. A function (in black) is convex if and only if its epigraph, which is the region above its graph (in green), is a convex set.

  5. Convex function - Wikipedia

    en.wikipedia.org/wiki/Convex_function

    This characterization of convexity is quite useful to prove the following results. A convex function f {\displaystyle f} of one real variable defined on some open interval C {\displaystyle C} is continuous on C . {\displaystyle C.} f {\displaystyle f} admits left and right derivatives , and these are monotonically non-decreasing .

  6. List of convexity topics - Wikipedia

    en.wikipedia.org/wiki/List_of_convexity_topics

    Complex convexity — extends the notion of convexity to complex numbers. Convex analysis - the branch of mathematics devoted to the study of properties of convex functions and convex sets, often with applications in convex minimization. Convex combination - a linear combination of points where all coefficients are non-negative and sum to 1 ...

  7. K-convexity in Rn - Wikipedia

    en.wikipedia.org/wiki/K-Convexity_in_Rn

    The concept of K-convexity generalizes K-convexity introduced by Scarf (1960) [2] to higher dimensional spaces and is useful in multiproduct inventory problems with fixed setup costs. Scarf used K-convexity to prove the optimality of the (s, S) policy in the single product case. Several papers are devoted to obtaining optimal policies for ...

  8. Convex measure - Wikipedia

    en.wikipedia.org/wiki/Convex_measure

    The classes of s-convex measures form a nested increasing family as s decreases to −∞" . or, equivalently {} {}.Thus, the collection of −∞-convex measures is the largest such class, whereas the 0-convex measures (the logarithmically concave measures) are the smallest class.

  9. Closed convex function - Wikipedia

    en.wikipedia.org/wiki/Closed_convex_function

    If : is a continuous function and is closed, then is closed.; If : is a continuous function and is open, then is closed if and only if it converges to along every sequence converging to a boundary point of .