To understand one-dimensional continuous fitness landscapes by drift analysis

Jun HE, Xin YAO, Qingfu ZHANG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

5 Citations (Scopus)


This paper shows that we could describe the characteristics of easy and hard fitness landscapes in one-dimensional continuous space by drift analysis. The work expends the existing results in the discrete space into the continue space. A fitness landscape, in this paper, is regarded as the behaviour of an evolutionary algorithm on fitness functions. Based on the drift analysis, easy fitness landscapes are thought to be a "short-distance" landscape, which is easy for the evolutionary algorithm to find the optimal point; and hard fitness landscapes then are as a far-distance landscape, which the evolutionary algorithm had to spend a long time to find the optimal point.
Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Number of pages6
Publication statusPublished - 2004
Externally publishedYes


  • Analysis of Algorithms
  • Evolutionary Algorithms
  • First Hitting Time
  • Fitness Landscapes


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