A CONTINUOUS-TIME MIXED-INTEGER LINEAR-PROGRAMMING MODEL FOR SHORT-TERM SCHEDULING OF MULTISTAGE BATCH PLANTS

Citation
Jm. Pinto et Ie. Grossmann, A CONTINUOUS-TIME MIXED-INTEGER LINEAR-PROGRAMMING MODEL FOR SHORT-TERM SCHEDULING OF MULTISTAGE BATCH PLANTS, Industrial & engineering chemistry research, 34(9), 1995, pp. 3037-3051
Citations number
26
Categorie Soggetti
Engineering, Chemical
ISSN journal
08885885
Volume
34
Issue
9
Year of publication
1995
Pages
3037 - 3051
Database
ISI
SICI code
0888-5885(1995)34:9<3037:ACMLMF>2.0.ZU;2-W
Abstract
The problem of short term scheduling of batch plants consists of deter mining the optimal production policy for satisfying the production dem ands for different products at due dates and/or at the end of a given time horizon. The objective of this work is to propose an optimization model and solution method to the short term scheduling of batch plant s with multiple stages which may contain equipment in parallel. A larg e scale mixed integer linear programming (MILP) model with continuous time domain representation is proposed that relies on the use of paral lel time axes for units and tasks. Although in principle an LP-based b ranch and bound method can be used to solve the problem, there is a li mitation when the instances become large. The first solution strategy that is proposed consists of the use of preordering constraints. Furth ermore, a second strategy relies on a decomposition scheme for large s ystems which is based on the solution of an MILP model that minimizes total in process time in which assignments are determined and the subs equent solution of an LP to minimize earliness and to eliminate unnece ssary setups. Several examples are presented, including a large real w orld problem, to illustrate the performance of the model and solution method.