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LZW Encoding in Genetic Algorithm

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  • Worasait Suwannik

    (Kasetsart University, Thailand)

Abstract

To solve a problem using Genetic Algorithms (GAs), a solution must be encoded into a binary string. The length of the binary string represents the size of the problem. As the length of the binary string increases, the size of the search space also increases at an exponential rate. To reduce the search space, one approach is to use a compressed encoding chromosome. This paper presents a genetic algorithm, called LZWGA, that uses compressed chromosomes. An LZWGA chromosome must be decompressed using an LZW decompression algorithm before its fitness can be evaluated. By using compressed encoding, the search space is reduced dramatically. For one-million-bit problem, the search space of the original problem is 21000000 or about 9.90x10301029 points. When using a compressed encoding, the search space was reduced to 8.37x10166717 points. LZWGA can solve one-million-bit OneMax, RoyalRoad, and Trap functions.

Suggested Citation

  • Worasait Suwannik, 2011. "LZW Encoding in Genetic Algorithm," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 2(4), pages 25-36, October.
    • Handle: RePEc:igg:jaec00:v:2:y:2011:i:4:p:25-36
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