Genetic algorithm behaviour in the multi-criteria optimisation task

The study investigates genetic algorithm behaviour. A hypothesis is suggested which states that the genetic algorithm can be used not only for finding a single global optimum point but also for determining a whole parameter region. Two multi-criteria optimisation tasks are solved, with the behaviour of three different real number genetic algorithms being compared in the solution process. Real number genetic algorithm steps are described, and their meanings explained. Populations are compared graphically, after a definite number of generations (after the 1st, 8th, 16th, 100th generations). Explanations are suggested for differences in algorithm behaviour and causes of such differences.