Science and Technology Production
Article
Authorship
C.A. Méndez
;
J. Cerdá
Date
2000
Publishing House and Editing Place
PERGAMON-ELSEVIER SCIENCE LTD
Magazine
COMPUTERS AND CHEMICAL ENGINEERING,
vol. 24
(pp. 369-376)
PERGAMON-ELSEVIER SCIENCE LTD
Summary
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This paper is concerned with the short-term scheduling of a two-stage multiproduct batch plant where a number of intermediate products are processed to deliver to nearby end-product facilities. The common processing sequence involves a single stage with multiple parallel units and a subsequent storage stage. After processing, the batches of intermediate products are transferred to tanks of different capacities from which they are supplied to end-product facilities. Any storage tank is connected...
This paper is concerned with the short-term scheduling of a two-stage multiproduct batch plant where a number of intermediate products are processed to deliver to nearby end-product facilities. The common processing sequence involves a single stage with multiple parallel units and a subsequent storage stage. After processing, the batches of intermediate products are transferred to tanks of different capacities from which they are supplied to end-product facilities. Any storage tank is connected to a group of such facilities and sequentially allocated to different compatible products. Topology constraints restricting the interconnections among processing units and tanks are additional conditions to be considered. Intermediate requirements are given in terms of batches, some of them involving the same product but featuring different sizes and due shifts. Since a constant consumption rate is assumed throughout the due shift, then every batch will remain during such a period of time in the assigned tank. A continuous-time MILP mathematical model that accounts for sequence-dependent changeover times and multiple product deliveries at specified time intervals and, in addition, easily embed preordering conditions has been developed. The proposed formulation has been successfully applied to the solution of a large-scale industrial problem. The optimal schedule was found in a quite reasonable CPU time by solving a single MILP model featuring a much smaller size than previous approaches. Elsevier Science Ltd. All rights reserved.
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Key Words
SchedulingBatch plantOptimization models