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Introducing shallow knowledge in batch operations models

Authors
Journal
Computers & Chemical Engineering
0098-1354
Publisher
Elsevier
Publication Date
Volume
18
Identifiers
DOI: 10.1016/0098-1354(94)80081-2

Abstract

Abstract This paper explores two alternative methods to introduce experience and operating preferences during the automatic generation of MILP batch operation models: 1) The imposition of “hard” constraints, which reduce the size of the solution space by dropping task allocations; 2) The addition of “soft” constraints, that tend to preserve desired features of the resulting plan and avoid undesired ones.

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