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Efficient Resource Allocation with Noisy Functions

  • Arne Andersson
  • Per Carlsson
  • Fredrik Ygge
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2141)

Abstract

We consider resource allocation with separable objective functions defined over subranges of the integers. While it is well known that (the maximisation version of) this problem can be solved efficiently if the objective functions are concave, the general problem of resource allocation with functions that are not necessarily concave is difficult. In this paper we show that for a large class of problem instances with noisy objective functions the optimal solutions can be computed efficiently. We support our claims by experimental evidence. Our experiments show that our algorithm in hard and practically relevant cases runs up to 40 – 60 times faster than the standard method.

Keywords

Objective Function Resource Allocation Optimal Allocation Neighbourhood Search Aggregate Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    A. Andersson, P. Carlsson, and F. Ygge. Resource allocation with noisy functions. Technical Report 2000-017, Department of Information Technology, Uppsala University, July 2000. (Available from www.it.uu.se/research/reports/).
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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Arne Andersson
    • 1
  • Per Carlsson
    • 2
    • 3
  • Fredrik Ygge
    • 4
  1. 1.Computing Science Department, Information TechnologyUppsala UniversityUppsalaSweden
  2. 2.Computing Science Department, Information TechnologyUppsala UniversitySweden
  3. 3.Computer Science DepartmentLund UniversityLundSweden
  4. 4.Enersearch AB and Computing Science Department, Information TechnologyUppsala UniversityGothenburgSweden

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