Convex separable optimization is not much harder than linear optimization
Journal of the ACM (JACM)
The joint replenishment problem with general joint cost structures
Operations Research
Mathematics of Operations Research
About strongly polynomial time algorithms for quadratic optimization over submodular constraints
Mathematical Programming: Series A and B
On the computation of the nucleolus of a cooperative game
International Journal of Game Theory
Dynamic Scheduling via Polymatroid Optimization
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
Submodular Returns and Greedy Heuristics for Queueing Scheduling Problems
Operations Research
Locating tree-shaped facilities using the ordered median objective
Mathematical Programming: Series A and B
Cost Allocation for Joint Replenishment Models
Operations Research
Operations Research
IEEE Transactions on Information Theory
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In this paper we consider the problem of maximizing a separable concave function over a polymatroid. More specifically, we study the submodularity of its optimal objective value in the parameters of the objective function. This question is interesting in its own right and is encountered in many applications. But our research has been motivated mainly by a cooperative game associated with the well-known joint replenishment model. By applying our general results on polymatroid optimization, we prove that this cooperative game is submodular (i.e., its characteristic cost function is submodular) if the joint setup cost is a normalized and nondecreasing submodular function. Furthermore, the same result holds true for a more general one-warehouse multiple retailer game, which affirmatively answers an open question posed by Anily and Haviv [Anily, S., M. Haviv. 2007. The cost allocation problem for the first order interaction joint replenishment model. Oper. Res.55(2) 292--302].