GENETIC SOLVER OF OPTIMIZATION TASK OF MPC FOR OPTIMIZING CONTROL OF INTEGRATED QUANTITY AND QUALITY IN DRINKING WATER DISTRIBUTION SYSTEMS

The predictive integrated water quantity and quality yields better performance then different approaches. However, it requires solving a nonlinear, non-convex optimization problem. Therefore, a specialized optimization solver has to be used within designated time. In this paper a dedicated genetic algorithm specially designed in order to efficiently solve predictive optimization task is derived and the simulation results of the case study Gdynia drinking water distribution system are presented.