Cellular Genetic Algorithms

  • Xuewei Li
  • Jinpei Wu
  • Xueyan Li


In this chapter, we introduce the applications of cellular automata in genetic algorithms. In the traditional sense, genetic algorithms (GA) originated from Darwin’s evolution theory. Borrowing from the natural law of “survival of the fittest”, through the genetic operations of selection, crossover and mutation, the individual’s adaptability gets improved. One important feature of genetic algorithms is that the optimization process is not dependent on gradient information, which makes it especially suitable for dealing with complex and nonlinear problems which are difficult to be solved by general searching methods.


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Copyright information

© Beijing Jiaotong University Press and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Beijing Union UniversityBeijingChina
  2. 2.Wuyi UniversityJiangmenChina
  3. 3.Beijing Jiaotong universityBeijingChina

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