An Algorithm for Optimizing the Unsteady Chemical Processes by Simulated Annealing

In this paper, we propose an algorithm based on basic simulated annealing (SA) to optimize unsteady chemical systems. By parametrizing the control inputs, the system described by a set of differential-algebraic equations is first transferred into a nonlinear programming (NLP) problem. By using a linear function, we furthermore convert discretized control inputs and time grids into the control profile with a variable time length to improve numerical quality. Thus, the discretized control inputs and the corresponding execution time lengths will be considered as a set of decision variables. Then, these decision variables are globally determined by our algorithm with the help of a special integrator to optimize the performance index. In order to exhibit the facility of the proposed algorithm, several typical examples are provided.