Summary: We consider a profit maximization problem where we are asked to price a set of \(m\) items that are to be assigned to a set of \(n\) customers. The items can be represented as the edges of an undirected (multi)graph \(G\), where an edge multiplicity larger than one corresponds to multiple copies of the same item. Each customer is interested in purchasing a bundle of edges of \(G\), and we assume that each bundle forms a simple path in \(G\). Each customer has a known budget for her respective bundle, and is interested only in that particular bundle. The goal is to determine item prices and a feasible assignment of items to customers in order to maximize the total profit. When the underlying graph \(G\) is a path, we derive a fully polynomial time approximation scheme, complementing a recent NP-hardness result. If the underlying graph is a tree, and edge multiplicities are one, we show that the problem is polynomially solvable, contrasting its APX-hardness for the case of unlimited availability of items. However, if the underlying graph is a grid, and edge multiplicities are one, we show that it is even NP-complete to approximate the maximum profit to within a factor \(n^{1-\epsilon }\).
For the entire collection see [Zbl 1137.68005].