A Multiobjective Optimization Approach for the Simultaneous Single Line Scheduling and Control of CSTRs

Abstract

A new multiobjective optimization formulation dealing with simultaneous scheduling and control issues in single line processing systems is proposed. Objective functions featuring economic profit and dynamic performance are considered because normally they are in conflict. Because integer, continuous variables and process dynamic behavior are involved, the bicriterion optimization problem is cast in terms of a mixed-integer dynamic optimization (MIDO) problem. The Pareto front of each problem is computed using the ε-constraint method for handling multiobjective problems. The results indicate that improved optimal solutions can be obtained by using multiobjective optimization techniques instead of just simple merging of all the target objective functions into a single objective. The proposed multiobjective approach for handling scheduling and control problems is illustrated using three CSTR examples of varying nonlinear behavior.

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

“…The solution is achieved by iteration between MILP and NLP subproblems and Benders' decomposition. Gutierrez-Limon et al develop a multi-objective optimization approach for simultaneous scheduling and control of continuous chemical processes [40]. Benefit is demonstrated from using multi-objective approaches with Pareto fronts rather than combining economic and dynamic performance objectives into a single objective function.…”

Moving horizon approach of integrating scheduling and control for sequential batch processes

“…Using the collocation points, the continuous-time state and input trajectories satisfying the differential equations are discretized. The discretization procedure transforms the differential equation (16) into algebraic equations as…”

“…[1][2][3][4] As two major decision-making layers in the production hierarchy, integration of scheduling and control has attracted significant research efforts in recent years. [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] Compared with the traditional method where the scheduling problem and the control problem are solved sequentially, the integrated method can optimize the overall performance of the production process by making a better coordination between the subsystems.…”

Model-based multi-parametric programming strategies towards the integration of design, control and operational optimization

“…[70,119] Simultaneous/Decomposition (MI)DO schedule and P-PI-PID control [58,93,225,269] Simultaneous/Decomposition algorithms using control/dynamics aware scheduling models [42,122,370] Simultaneous/Decomposition algorithms via (MI)DO reformulation to (MI)NLP [161,183,184,277,335,336] Control theory in scheduling problems [146,147,277,362] Advanced control and (MI)NLP scheduling schemes [75,158,166,204,270] Scheduling under uncertainty [19,29,102,126,142,153] Review articles on scheduling and control and methodologies…”