Year: 2010
Type: preprint
Abstract: We develop a rounding method based on random walks in polytopes, which leads to improved approximation algorithms and integrality gaps for several assignment problems that arise in resource allocation and scheduling. In particular, it generalizes the work of Shmoys and Tardos on the generalized assignment problem to the setting where some jobs can be dropped. New concentration bounds for random bipartite matching are developed as well.
Source: arXiv (Cornell University)
Authors: Saha, Barna, Srinivasan, Aravind
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
Awards: EAGER: Probabilistic Models and Algorithms, AF: Small: Randomized Algorithms and Stochastic Models, CCF: Fundamental Algorithms for Data Management, CAREER: Efficient Fine-grained Algorithms, G6671297155, Collaborative Research: NeTS-NBD: An Integrated Approach to Computing Capacity and Developing Efficient Cross-Layer Protocols for Wireless Networks, ITR - (ASE+NHS) - (DMC+INT+SOC): Resilient Storage and Querying in Decentralized Networks, NetSE: Large: Collaborative Research: Contagion in Large Socio-Communication Networks
OpenAlex ID: W2952993429