Binary-real coding of solutions in genetic algorithms
The problem of solutions coding in genetic algorithms was reviewed in this paper. The main classes of solutions coding are presented. Advantages and disadvantages of binary coding and real coding in genetic algorithms have been analyzed. The main purpose of the research is to develop a new way of coding solutions in genetic algorithms. The method developed consists of two stages. Binary coding with the partition of solutions area into small intervals is applied during the first stage. Real coding is used at the second stage. This approach allows one to take advantages of both binary and real coding. Comparative analysis of the efficiency of the new coding method in genetic algorithms for optimization of complex functions is carried out. Efficiency analysis has shown that the use of binary-real coding in genetic algorithms can solve the optimization problem with a quite high degree of accuracy at medium computational overhead. Practical recommendations for using binary-real coding in various cases are presented.