Scheduling of non-sequential multipurpose batch processes under finite intermediate storage policy

Citation
Sb. Kim et al., Scheduling of non-sequential multipurpose batch processes under finite intermediate storage policy, COMPUT CH E, 24(2-7), 2000, pp. 1603-1610
Citations number
10
Categorie Soggetti
Chemical Engineering
Journal title
COMPUTERS & CHEMICAL ENGINEERING
ISSN journal
00981354 → ACNP
Volume
24
Issue
2-7
Year of publication
2000
Pages
1603 - 1610
Database
ISI
SICI code
0098-1354(20000715)24:2-7<1603:SONMBP>2.0.ZU;2-N
Abstract
In this study, we present a mathematical model for optimal scheduling of no n-sequential multipurpose batch processes under finite intermediate storage (FIS) policy. In non-sequential multipurpose batch processes, the producti on routes of products may be different from one another and may be in oppos ite direction. Consequently, in order to reduce idle time of units and to r aise the efficiency of process, we have to make operation sequences of prod ucts in each unit different by considering the production route of each pro duct. For the formulation of this problem, we represented the starting and finishing time of a task in each unit with two coordinates. One is based on products, and the other is based on operation sequences. Then, we matched the variables used in the two coordinates into one with binary variables an d logical constraints. We formulated this problem as an MILP model. Compare d with Jung, J. H., Lee, H., Yang, D. R. and Lee, I. (1994) [Completion tim es and optimal scheduling for serial multi-product processes with transfer and setup times in zero wait (ZW) policy. Computers & Chemical Engineering, 18(6), 537] and Kim, M. S., Jung, J. H. and Lee, I. (1996) [Optimal schedu ling of multiproduct batch processes for various intermediate storage polic ies. Industrial Engineering & Chemical Research, 27, 1840] who used an MINL P model for multiproduct scheduling problems, we suggest an MILP model, eve n though we handle sequence dependent setup times in multipurpose processes . Therefore, the proposed model can guarantee the optimality of the solutio ns. We applied this model to two examples to show the effectiveness of the model. The MILP solver we used to solve these problems is GAMS/OSL and H/W is IBM RS/6000 (model 350). (C) 2000 Elsevier Science Ltd. All rights reser ved.