The Simulated Greedy Algorithm for Several Submodular Matroid Secretary Problems

TL;DR

This paper introduces a general algorithm for submodular matroid secretary problems, achieving constant competitive ratios for laminar and transversal matroids, and improves results for linear valuation functions.

Contribution

It presents a unified algorithm for submodular matroid secretary problems with constant competitive ratios, extending to complex matroid intersections and improving linear case bounds.

Findings

Constant competitive algorithms for laminar and transversal matroids.

Applicable to intersections of a constant number of laminar matroids.

Improved competitive ratio of 9.6 for linear valuations on laminar matroids.

Abstract

We study the matroid secretary problems with submodular valuation functions. In these problems, the elements arrive in random order. When one element arrives, we have to make an immediate and irrevocable decision on whether to accept it or not. The set of accepted elements must form an {\em independent set} in a predefined matroid. Our objective is to maximize the value of the accepted elements. In this paper, we focus on the case that the valuation function is a non-negative and monotonically non-decreasing submodular function. We introduce a general algorithm for such {\em submodular matroid secretary problems}. In particular, we obtain constant competitive algorithms for the cases of laminar matroids and transversal matroids. Our algorithms can be further applied to any independent set system defined by the intersection of a {\em constant} number of laminar matroids, while still achieving constant competitive ratios. Notice that laminar matroids generalize uniform matroids and partition matroids. On the other hand, when the underlying valuation function is linear, our algorithm achieves a competitive ratio of 9.6 for laminar matroids, which significantly improves the previous result.