Efficient Resource Allocation with Noisy Functions
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.
KeywordsObjective Function Resource Allocation Optimal Allocation Neighbourhood Search Aggregate Function
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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/).
- A. Andersson and F. Ygge. Managing large scale computational markets. In H. El-Rewini, editor, Proceedings of the Software Technology track of the 31th Hawaiian International Conference on System Sciences (HICSS31), volume VII, pages 4–14. IEEE Computer Society, Los Alamos, January 1998. ISBN 0-8186-8251-5, ISSN 1060-3425, IEEE Catalog Number 98TB100216. (Available from http://www.enersearch.se/ygge).Google Scholar
- Arne Andersson and Fredrik Ygge. Efficient resource allocation with non-concave objective functions. Accepted for publication in Computational Optimization and Applications, 2001. (A preprint version is available as a research report from http://www.enersearch.se).
- Thomas H. Cormen, Charles E. Leiserson, and Ronald L. Rivest. Introduction to Algorithms. MIT Press, Cambridge, Massachusetts London, England, 1989.Google Scholar
- R. Fletcher. Practical Methods of Optimization. John Wiley & Sons, 1987. Second Edition.Google Scholar