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

被引:21
作者
Kim, SB [1 ]
Lee, HK
Lee, IB
Lee, ES
Lee, B
机构
[1] POSTECH, Dept Chem Engn, Ctr Automat Res, Pohang, South Korea
[2] Dongguk Univ, Dept Chem Engn, Seoul, South Korea
关键词
scheduling; multipurpose process; finite intermediate storage; MILP model;
D O I
10.1016/S0098-1354(00)00548-2
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this study, we present a mathematical model for optimal scheduling of non-sequential multipurpose batch processes under finite intermediate storage (FIS) policy. In non-sequential multipurpose batch processes, the production routes of products may be different from one another and may be in opposite direction. Consequently, in order to reduce idle time of units and to raise the efficiency of process, we have to make operation sequences of products in each unit different by considering the production route of each product. 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 and logical constraints. We formulated this problem as an MILP model. Compared with Jung, J. H., Lee, H., Yang, D. R. and Lee, I. (1994) [Completion times 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 scheduling of multiproduct batch processes for various intermediate storage policies. Industrial Engineering & Chemical Research, 27, 1840] who used an MINLP model for multiproduct scheduling problems, we suggest an MILP model, even though we handle sequence dependent setup times in multipurpose processes. Therefore, the proposed model can guarantee the optimality of the solutions. 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 reserved.
引用
收藏
页码:1603 / 1610
页数:8
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