Production Planning Using Simulation and Genetic Algorithms in Multi-criteria Scheduling Optimization

This paper describes an approach to using simulation and visualization of discrete event oriented simulation models for multi-criteria scheduling optimization with genetic algorithms. A simulation model was used for fitness function computation of genetic algorithm results, as well as for visual representation of process behavior of a chosen schedule following genetic algorithm optimization. In this way, with the help of simulation and visualization, an additional verification of a schedule’s suitability was conducted on optimization results. The described methodology provides the planner with a quick and efficient scheduling method and enables him/her to experiment and decide which of the suitable solutions will become the production plan. The scheduling system is composed of a business information system a database, a discrete event simulation model and a scheduling algorithm. The purpose of the integrated system is to help operative management personnel with production scheduling and planning. By comparing various scheduling methods, we established that the system utilizing genetic algorithms and simulation yielded from 5% to 15% better scheduling within a shorter time compared to manual scheduling.