An Introduction to Proof Techniques for Bin-Packing Approximation Algorithms

  • E. G. CoffmanJr.
Part of the NATO Advanced Study Institutes Series book series (ASIC, volume 84)


Introductory Remarks — Upon introducing a seemingly small change or generalization into either the model or an approximation algorithm for a previously studied bin packing problem, it has been common to find that very little of the analysis of the original problem can be exploited in analyzing the new problem. Such experiences may suggest that the mathematics of bin packing does not contain a central, well-structured theory that provides powerful, broadly applicable techniques for the analysis of approximation algorithms. It would be difficult to repudiate completely such an observation, but we hope to show that the extent to which it is true is largely inevitable. Specifically, our aim in this brief tutorial extension of the survey in [GJ] will be to explain somewhat informally certain techniques that do enjoy a moderately broad applicability, while making it clear where the novelty and perhaps ingenuity of the approach to an individual problem may be required.


Weighting Function Approximation Algorithm Performance Ratio Optimum Packing Optimization Rule 
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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Copyright information

© D. Reidel Publishing Company 1982

Authors and Affiliations

  • E. G. CoffmanJr.
    • 1
  1. 1.Bell LaboratoriesMurray HillUSA

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