Production campaign planning including grade transition sequencing and dynamic optimization

Abstract A method is presented for solving a production optimization problem consisting of the determination of transition trajectories, operating points, and sequencing for manufacturing a set of products. The complete production problem is split up into a dynamic optimization problem (primal problem), and a mixed-integer linear problem (master problem), which is related to the sequencing/scheduling. Information for construction of the master problem is obtained from the solutions of the primal problems. The complete problem is solved through an iterative procedure. The method is a modular and application-specific alternative to standard methods such as Benders Decomposition and Outer Approximation, and offers advantages in comparison to these. The modularity of the approach provides for flexibility in choosing the optimization tools. The method is illustrated by determining optimal production campaigns for a polymerization process.

[1]  Ignacio E. Grossmann,et al.  Assignment and sequencing models for thescheduling of process systems , 1998, Ann. Oper. Res..

[2]  J. Macgregor,et al.  Optimal Grade Transitions in a Gas Phase Polyethylene Reactor , 1992 .

[3]  Jose M. Pinto,et al.  Mixed integer nonlinear programming techniques for the short term scheduling of oil refineries , 2003 .

[4]  Alberto Bemporad,et al.  Control of systems integrating logic, dynamics, and constraints , 1999, Autom..

[5]  I. Grossmann,et al.  A combined penalty function and outer-approximation method for MINLP optimization : applications to distillation column design , 1989 .

[6]  I. Grossmann.  Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques , 2002 .

[7]  Hiranmayee Vedam,et al.  A framework for managing transitions in chemical plants , 2005, Comput. Chem. Eng..

[8]  Paul I. Barton,et al.  Mixed-integer dynamic optimization I: problem formulation , 1999 .

[9]  Jay H. Lee,et al.  An introduction to a dynamic plant-wide optimization strategy for an integrated plant , 2004, Comput. Chem. Eng..

[10]  L. Biegler,et al.  Large-scale dynamic optimization for grade transitions in a low density polyethylene plant , 2002 .

[11]  Manfred Morari,et al.  Anwendung von modellbasierter prädiktiver Regelung und Methoden der hybriden Systeme zur optimalen Produktionsplanung (Using Model Predictive Control and Hybrid Systems for Optimal Scheduling of Industrial Processes) , 2003 .

[12]  Efstratios N. Pistikopoulos,et al.  Optimal grade transition campaign scheduling in a gas-phase polyolefin FBR using mixed integer dynamic optimization , 2003 .

[13]  Rüdiger Franke,et al.  Applying New Numerical Algorithms to the Solution of Discrete-Time Optimal Control Problems , 1997 .

[14]  T. Backx,et al.  Grade-change control using INCA model predictive controller: application on a Dow polystyrene process model , 2003, Proceedings of the 2003 American Control Conference, 2003..

[15]  L. Biegler,et al.  Dynamic Optimization in the Design and Scheduling of Multiproduct Batch Plants , 1996 .

[16]  Kevin Warwick,et al.  Computer Intensive Methods in Control and Signal Processing: The Curse of Dimensionality , 1997 .

[17]  Efstratios N. Pistikopoulos,et al.  Optimal grade transition and selection of closed-loop controllers in a gas-phase olefin polymerization fluidized bed reactor , 2003 .

[18]  Eric R. Zieyel.  Operations research : applications and algorithms , 1988 .

[19]  J. Pekny,et al.  Exact solution of the no-wait flowshop scheduling problem with a comparison to heuristic methods , 1991 .

[20]  R. Sargent,et al.  Solution of a Class of Multistage Dynamic Optimization Problems. 2. Problems with Path Constraints , 1994 .

[21]  Efstratios N. Pistikopoulos,et al.  Optimal design of dynamic systems under uncertainty , 1996 .

[22]  Tapio Westerlund,et al.  Comparisons of solving a chromatographic separation problem using MINLP methods , 2004, Comput. Chem. Eng..

[23]  R. L. Tousain,et al.  Dynamic optimization in business-wide process control , 2002 .

[24]  W. Marquardt,et al.  Mixed‐logic dynamic optimization applied to batch distillation process design , 2003 .

[25]  Francis J. Doyle,et al.  Polymer grade transition control using advanced real-time optimization software , 2004 .

[26]  Efstratios N. Pistikopoulos,et al.  New algorithms for mixed-integer dynamic optimization , 2003, Comput. Chem. Eng..