Exact algorithms for budgeted prize-collecting covering subgraph problems

We introduce a class of budgeted prize-collecting covering subgraph problems. For an input graph with prizes on the vertices and costs on the edges, the aim of these problems is to find a connected subgraph such that the cost of its edges does not exceed a given budget and its collected prize is maximum. A vertex prize is collected when the vertex is visited. Moreover, a prize is also collected if the vertex is covered, where an unvisited vertex is covered by a visited one if the latter belongs to the former’s covering set. A capacity limit is imposed on the number of vertices that can be covered by the same visited vertex. Potential application areas include network design and intermodal transportation. We develop a branch-and-cut framework and a Benders decomposition for the exact solution of the problems in this class. We observe that the former algorithm results in shorter computational times on average, but also that the latter can outperform the former for specific instance settings. Finally, we validate our algorithmic frameworks for the cases where the subgraph is a cycle and a tree, and for these two cases we also identify novel symmetry-breaking inequalities. •A generic mixed-integer programming model is proposed for budgeted prize-collecting covering subgraph problems.•A branch-and-cut and a Benders decomposition are devised and compared.•Symmetry-breaking inequalities for the tree and the cycle subgraph cases are identified.•The algorithms are tested on a pool of more than 800 instances.•The Benders decomposition outperforms the branch-and-cut when the budget value is low.