ABSTRACT
The chapter discusses issues concerning application of genetic algorithms as a highly efficient method of solving multi-dimensional optimization problems, among which the search for optimum solutions aimed at reduction of workers’ exposure to noise can be ranked. In the introduction to the topic, basic concepts of the theory of genetic algorithms are presented, and then (based on literature of the subject) examples are given of possible application of genetic algorithms in the domain of research on noise and exposure to noise control. Further, implementation of the genetic algorithm method is illustrated in detail on an example of optimization of noise sources and workstations arrangement oriented at reduction of workers’ exposure to noise. The example is used to demonstrate the methods of coding optimization process variables, defining the fitness function representing the quality of the solution, and defining the penalty function representing constraints imposed on given optimization problem. The implementation example includes presentation of a computer application supporting optimization of noise sources and workstations arrangement based on the presented algorithm and results of simulations performed with the use of the application.
