K-convex functions, first introduced by Scarf, are a special weakening of the concept of convex function which is crucial in the proof of the optimality of the                     (        s        ,        S        )                 policy in inventory control theory. The policy is characterized by two numbers s and S,                     S        ≥        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.
Two equivalent definitions are as follows:
A function                     g        :                  R                →                  R                         is K-convex if
                    g        (        u        )        +        z                  [                                                    g                (                u                )                −                g                (                u                −                b                )                            b                                ]                ≤        g        (        u        +        z        )        +        K                for any                     u        ,        z        ≥        0        ,                 and                     b        >        0                .
A function                     g        :                  R                →                  R                         is K-convex if
                    g        (        λ        x        +                                            λ              ¯                                      y        )        ≤        λ        g        (        x        )        +                                            λ              ¯                                      [        g        (        y        )        +        K        ]                for all                     x        ≤        y        ,        λ        ∈        [        0        ,        1        ]                , where                                                         λ              ¯                                      =        1        −        λ                .
This definition admits a simple geometric interpretation related to the concept of visibility. Let                     a        ≥        0                . A point                     (        x        ,        f        (        x        )        )                 is said to be visible from                     (        y        ,        f        (        y        )        +        a        )                 if all intermediate points                     (        λ        x        +                                            λ              ¯                                      y        ,        f        (        λ        x        +                                            λ              ¯                                      y        )        )        ,        0        ≤        λ        ≤        1                 lie below the line segment joining these two points. Then the geometric characterization of K-convexity can be obtain as:
A function 
                    g                 is 
K-convex if and only if 
                    (        x        ,        g        (        x        )        )                 is visible from 
                    (        y        ,        g        (        y        )        +        K        )                 for all 
                    y        ≥        x                .
It is sufficient to prove that the above definitions can be transformed to each other. This can be seen by using the transformation
                    λ        =        z                  /                (        b        +        z        )        ,                x        =        u        −        b        ,                y        =        u        +        z        .                If                     g        :                  R                →                  R                         is K-convex, then it is L-convex for any                     L        ≥        K                . In particular, if                     g                 is convex, then it is also K-convex for any                     K        ≥        0                .
If                               g                      1                                   is K-convex and                               g                      2                                   is L-convex, then for                     α        ≥        0        ,        β        ≥        0        ,                g        =        α                  g                      1                          +        β                  g                      2                                   is                     (        α        K        +        β        L        )                -convex.
If                     g                 is K-convex and                     ξ                 is a random variable such that                     E                  |                g        (        x        −        ξ        )                  |                <        ∞                 for all                     x                , then                     E        g        (        x        −        ξ        )                 is also K-convex.
If                     g        :                  R                →                  R                         is a continuous K-convex function and                     g        (        y        )        →        ∞                 as                               |                y                  |                →        ∞                , then there exit scalars                     s                 and                     S                 with                     s        ≤        S                 such that
                    g        (        S        )        ≤        g        (        y        )                , for all                     y        ∈                  R                        ;                    g        (        S        )        +        K        =        g        (        s        )        <        g        (        y        )                , for all                     y        <        s                ;                    g        (        y        )                 is a decreasing function on                     (        −        ∞        ,        s        )                ;                    g        (        y        )        ≤        g        (        z        )        +        K                 for all                     y        ,        z                 with                     s        ≤        y        ≤        z                .