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
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.