A Genetic Algorithm to Minimize Chromatic Entropy

  • Greg Durrett
  • Muriel Médard
  • Una-May O’Reilly
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6022)

Abstract

We present an algorithmic approach to solving the problem of chromatic entropy, a combinatorial optimization problem related to graph coloring. This problem is a component in algorithms for optimizing data compression when computing a function of two correlated sources at a receiver. Our genetic algorithm for minimizing chromatic entropy uses an order-based genome inspired by graph coloring genetic algorithms, as well as some problem-specific heuristics. It performs consistently well on synthetic instances, and for an expositional set of functional compression problems, the GA routinely finds a compression scheme that is 20-30% more efficient than that given by a reference compression algorithm.

Keywords

chromatic entropy functional compression graph coloring 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Greg Durrett
    • 1
  • Muriel Médard
    • 2
  • Una-May O’Reilly
    • 1
  1. 1.Computer Science and Artificial Intelligence Laboratory 
  2. 2.Research Laboratory for ElectronicsMassachusetts Institute of Technology 

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