LZW Chromosome Encoding in Estimation of Distribution Algorithms

نویسندگان

  • Orawan Watchanupaporn
  • Worasait Suwannik
چکیده

Estimation of distribution algorithm (EDA) can solve more complicated problems than its predecessor (Genetic Algorithm). EDA uses various methods to probabilistically model a group of highly fit individuals. Calculating the model in sophisticated EDA is very time consuming. To reduce the model building time, the authors propose compressed chromosome encoding. A chromosome is encoded using a format that can be decompressed by the Lempel-Ziv-Welch (LZW) algorithm. The authors combined LZW encoding with various EDAs and termed the class of algorithms Lempel-Ziv-Welch Estimation of Distribution Algorithms (LZWEDA). Experimental results show that LZWEDA significantly outperforms the original EDA. Finally, the authors analyze how LZW encoding transforms a fitness landscape. LZW Chromosome Encoding in Estimation of Distribution Algorithms

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عنوان ژورنال:
  • IJAEC

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2013