The Use of Genetic Algorithms for Optimizing the Reliability of a Danger Control System Design

In this paper, we propose a genetic algorithms procedure for solving optimal danger control system design where choices on the type of components to be used and their assembly configuration are driven by reliability objective with the economic costs associated to the design implementation, system construction and future operation. The genetic algorithm considers a population of chromosomes, each one encoding a different alternative design solution. For a given design solution, the system performance over a specified mission time is evaluated in terms of a pre-defined reliability function. This latter constitutes the objective function to be maximized by the genetic algorithm through the evolution of the successive generations of the population in conditions of not overlapping a cost constraint for the system.