Abstract
In the generalized budgeted submodular set function maximization problem, we are given a ground set of elements and a set of bins. Each bin has its own cost and the cost of each element depends on its associated bin. The goal is to find a subset of elements along with an associated set of bins such that the overall costs of both is at most a given budget, and the profit is maximized. We present an algorithm that guarantees a -approximation, where is the approximation factor of an algorithm for a sub-problem. If the costs satisfy a specific condition, we provide a polynomial-time algorithm that gives us , while for the general case we design an algorithm with.
We extend our results providing a bi-criterion approximation algorithm where we can spend an extra budget up to a factor
to guarantee a -approximation.
We extend our results providing a bi-criterion approximation algorithm where we can spend an extra budget up to a factor
to guarantee a -approximation.
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 104741 |
| Seitenumfang | 13 |
| Fachzeitschrift | Information and Computation |
| Jahrgang | 281 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Dez. 2021 |
ÖFOS 2012
- 102033 Data Mining
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