An improved approximation algorithm for resource allocation

Abstract

We study the problem of finding a most profitable subset of n given tasks, each with a given start and finish time as well as profit and resource requirement, that at no time exceeds the quantity B of available resource. We show that this NP-hard Resource Allocation problem can be (1/2 − ε)-approximated in randomized polynomial time, which improves upon earlier approximation results.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 01, 2011
Source ID
10.1145/2000807.2000816

Entities

People

  • Amit Chakrabarti
  • Gruia Calinescu
  • Howard Karloff
  • Yuval Rabani

Organizations

  • Army Research Office
  • Bulgarian Science Fund
  • Dartmouth College
  • EU Business School
  • Hebrew University of Jerusalem
  • Illinois Institute of Technology
  • Israel Science Foundation
  • National Science Foundation

Tags

Fields of Study

  • Computer science

Readers

  • Graph Algorithms and Convex Optimization.
  • Life Cycle Cost Analysis
  • Systems Analysis and Design