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A Mildly Exponential Time Algorithm for Approximating the Number of Solutions to a Multidimensional Knapsack Problem

Published online by Cambridge University Press:  12 September 2008

Martin Dyer ,
Alan Frieze ,
Ravi Kannan ,
Ajai Kapoor ,
Ljubomir Perkovic  and
Umesh Vazirani
Martin Dyer
Affiliation:
University of Leeds, Leeds LS2 9JT, UK
Alan Frieze
Affiliation:
Carnegie Mellon University, Pittsburgh PA15213, USA
Ravi Kannan
Affiliation:
Carnegie Mellon University, Pittsburgh PA15213, USA
Ajai Kapoor
Affiliation:
Carnegie Mellon University, Pittsburgh PA15213, USA
Ljubomir Perkovic
Affiliation:
Carnegie Mellon University, Pittsburgh PA15213, USA
Umesh Vazirani
Affiliation:
University of California, Berkeley CA94320, USA
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Abstract

We describe a time randomized algorithm that estimates the number of feasible solutions of a multidimensional knapsack problem within 1 ± ε of the exact number. (Here r is the number of constraints and n is the number of integer variables.) The algorithm uses a Markov chain to generate an almost uniform random solution to the problem.

Information

Type
Research Article
Information
Combinatorics, Probability and Computing , Volume 2 , Issue 3 , September 1993 , pp. 271 - 284
Copyright
Copyright © Cambridge University Press 1993

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