Substitutes and complements in constrained linear models
SIAM Journal on Algebraic and Discrete Methods
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Qualitative Sensitivity Analysis in Monotropic Programming
Mathematics of Operations Research
Mathematical Programming: Series A and B
M-Convex Function on Generalized Polymatroid
Mathematics of Operations Research
Regular Article: Extension of M-Convexity and L-Convexity to Polyhedral Convex Functions
Advances in Applied Mathematics
Relationship of M-/L-convex functions with discrete convex functions by Miller and Favati-Tardella
Discrete Applied Mathematics - Special issue on selected papers from First Japanese-Hungarian Symposium for Discrete Mathematics and its Applications
Discrete Applied Mathematics - Submodularity
A Note on Kelso and Crawford's Gross Substitutes Condition
Mathematics of Operations Research
Conjugacy relationship between M-convex and L-convex functions in continuous variables
Mathematical Programming: Series A and B
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We study combinatorial properties of the optimal value function of the network flow problem. It is shown by Gale-Politof [Substitutes and complements in networks flow problems, Discrete Appl. Math. 3 (1981) 175-186] that the optimal value function has submodularity and supermodularity w.r.t. problem parameters such as weights and capacities. In this paper we shed a new light on this result from the viewpoint of discrete convex analysis to point out that the submodularity and supermodularity are naturally implied by discrete convexity, called M-convexity and L-convexity, of the optimal value function.