Developing genetic algorithms for minimizing occupational risk related to exposure to noise in manufacturing enterprises

The task consisted in proposing a method of minimizing occupational risk related to exposure to noise in the working environment with the use of genetic algorithms. It is based on acoustic models of the working environment. Software for simulation tests was developed. The functions of a genetic algorithm were implemented in it. A procedure for the simulations tests was developed, too. It was verified using as an example minimizing exposure to noise with the organizational method.The software for simulation tests that was developed during the project was modified and further developed. This included implementation of binary coding of floating point parameters in the genetic algorithm, the development of a user interface by adding elements of visualization of simulation tests and addition of scripts with parameters of models of the acoustic working environment that makes more effective use of the software possible .To consider in the genetic algorithm limitations related to the location of noise sources and workstations, which can be present in the real working environment, the physical possibility to carry out the solutions obtained with the use of the genetic algorithm and to consider the cost of installing machines and the cost of rotating workers, the function of a penalty was introduced. It modifies adaptation so as to eliminate bad solutions.Thus it was possible to formulate guidelines for designers of computer tools assisting in occupational safety and health management with respect to minimizing occupational risk related to exposure to noise.