Machine coded genetic algorithms for real-valued optimization problems CRAN Task View: Optimization (http://CRAN.R-project.org/view=Optimization) Machine coded genetic algorithm (MCGA) is a fast tool for real-valued optimization problems. It uses the byte representation of variables rather than real-values. It performs the classical crossover operations (uniform) on these byte representations. Mutation operator is also similar to classical mutation operator, which is to say, it changes a randomly selected byte value of a chromosome by +1 or -1 with probability 1/2. In MCGAs there is no need for encoding-decoding process and the classical operators are directly applicable on real-values. It is fast and can handle a wide range of a search space with high precision. Using a 256-unary alphabet is the main disadvantage of this algorithm but a moderate size population is convenient for many problems. Package also includes multi_mcga function for multi objective optimization problems. This function sorts the chromosomes using their ranks calculated from the non-dominated sorting algorithm. Software Mehmet Hakan Satman <mhsatman@istanbul.edu.tr> Mehmet Hakan Satman GPL 2012-01-09 application/tgz http://CRAN.R-project.org/package=mcga