Interactive genetic algorithms with individual fitness not assigned by human

Dunwei GONG, Xin YAO, Jie YUAN

Research output: Journal PublicationsJournal Article (refereed)peer-review

19 Citations (Scopus)


Interactive genetic algorithms (IGAs) are effective methods to solve optimization problems with implicit or fuzzy indices. But human fatigue problem, resulting from evaluation on individuals and assignment of their fitness, is very important and hard to solve in IGAs. Aiming at solving the above problem, an interactive genetic algorithm with an individual fitness not assigned by human is proposed in this paper. Instead of assigning an individual fitness directly, we record time to choose an individual from a population as a satisfactory or unsatisfactory one according to sensitiveness to it, and its fitness is automatically calculated by a transformation from time space to fitness space. Then subsequent genetic operation is performed based on this fitness, and offspring is generated. We apply this algorithm to fashion design, and the experimental results validate its efficiency. © J.UCS.
Original languageEnglish
Pages (from-to)2464-2480
Number of pages17
JournalJournal of Universal Computer Science
Issue number13
Publication statusPublished - 2009
Externally publishedYes


  • Genetic algorithm
  • Human fatigue
  • Individual fitness
  • Interactive genetic algorithm
  • Optimization


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