Minimum Cost Adaptive Submodular Cover

08/17/2022
by   Yubing Cui, et al.
0

We consider the problem of minimum cost cover of adaptive-submodular functions, and provide a 4(ln Q+1)-approximation algorithm, where Q is the goal value. This bound is nearly the best possible as the problem does not admit any approximation ratio better than ln Q (unless P=NP). Our result is the first O(ln Q)-approximation algorithm for this problem. Previously, O(ln Q) approximation algorithms were only known assuming either independent items or unit-cost items. Furthermore, our result easily extends to the setting where one wants to simultaneously cover multiple adaptive-submodular functions: we obtain the first approximation algorithm for this generalization.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/02/2019

An Efficient Evolutionary Algorithm for Minimum Cost Submodular Cover

In this paper, the Minimum Cost Submodular Cover problem is studied, whi...
research
08/02/2021

Hardness and Approximation of Submodular Minimum Linear Ordering Problems

The minimum linear ordering problem (MLOP) seeks to minimize an aggregat...
research
11/16/2021

The Stochastic Boolean Function Evaluation Problem for Symmetric Boolean Functions

We give two approximation algorithms solving the Stochastic Boolean Func...
research
06/30/2021

The Power of Adaptivity for Stochastic Submodular Cover

In the stochastic submodular cover problem, the goal is to select a subs...
research
12/27/2019

A Water-Filling Primal-Dual Algorithm for Approximating Non-Linear Covering Problems

Obtaining strong linear relaxations of capacitated covering problems con...
research
11/30/2019

Improved Approximation Algorithms for Inventory Problems

We give new approximation algorithms for the submodular joint replenishm...
research
03/02/2023

Pandora's Problem with Combinatorial Cost

Pandora's problem is a fundamental model in economics that studies optim...

Please sign up or login with your details

Forgot password? Click here to reset