Distributed global optimization in complex control systems; case study results

The objective of the paper is to present the advantages of distributed implementations of global optimization algorithms while improving the performance of control mechanisms in complex systems. As an example of such systems, the authors use a multireservoir water system working under flood conditions. The optimization problem consists in determining, for all reservoirs, parameters through which a control center influences releases from the reservoirs. Since this problem involves cumbersome calculations (e.g. numerical simulations), it seems reasonable to apply nongradient global optimization methods and parallel supercomputers for its solution. In the paper, the authors describe how the proper optimization algorithm was chosen and to what extent its distributed implementation improved the efficiency of the control system.