J.L.D. Faco' (Brazil)
Nonlinear Programming, optimal control, and GRG method
The complexity of many decision problems may require the formulation of nonlinear models able to consider in a more realistic way its physical, chemical, economical, and biological properties. With modern sophistication of data measurements and structures, and computing capabilities, the models can represent real problems with less aggregation levels, improving their dimensions by larger number of variables and parameters submitted to more constraints to exhibit feasible solutions to practical problems. Models with dynamic structure as: (i) marine multi-species fishery management, and (ii) optimal electric energy short-term generation scheduling for complex hydro-thermal systems can be constructed. Coupled sets of discrete-time difference equations describe the interacting dynamics of natural resources and the environment, and optimal control theory can be applied to build model structure and to parameters estimation, but the increase in model complexities as nonlinearities, time delays, supplementary inequality constraints on the state and the control variables imply critical numerical difficulties. Reliable Nonlinear Programming numerical optimization methods can deal with these questions efficiently.
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