evolutionary strategies

Evolution strategy is a heuristic optimization method in the section of evolutionary algorithms based on adaptation and evolution. The method was developed in 1964 by the German scientist Ingo Rechenberg and later developed by Hans-Paul Schwefel and others. ^{[1] [2]}

Basic principles

The evolutionary strategy is similar to the genetic algorithm, but there are several significant differences.

Evolutionary strategy operates with vectors of real numbers. When searching for a solution in evolutionary strategy, there is a first mutation and crossing of individuals (see the mutation and crossing operators in the article Genetic Algorithm) to obtain descendants, then deterministic selection occurs without repeating the best individuals from the general generation of parents and descendants. As a mutation, the addition of a normally distributed random variable to each component of a vector is often used. In this case, the parameters of the normal distribution are self-adapted during the execution of the algorithm.

see also

• Genetic algorithm
• Evolutionary Algorithms