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Decomposition techniques for the solution of large‐scale scheduling problems
Author(s) -
Bassett Matthew H.,
Pekny Joseph F.,
Reklaitis Gintaras V.
Publication year - 1996
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690421209
Subject(s) - scheduling (production processes) , decomposition , computer science , strengths and weaknesses , heuristic , mathematical optimization , time horizon , scale (ratio) , industrial engineering , operations research , engineering , mathematics , artificial intelligence , chemistry , philosophy , physics , organic chemistry , epistemology , quantum mechanics
With increased product specialization within the chemical‐processing industries, the ability to obtain production schedules for complex facilities is at a premium. This article discusses ways of quickly obtaining solutions for industrially relevant, large‐scale scheduling problems. A number of time‐based decomposition approaches are presented along with their associated strengths and weaknesses. It is shown that the most promising of the approaches utilizes a reverse rolling window in conjunction with a disaggregation heuristic. In this method, only a small subsection of the horizon is dealt with at a time, thus reducing the combinatorial complexity of the problem. Resource‐ and task‐unit‐based decompositions are also discussed as possible approaches to reduce the problem to manageable proportions. A number of examples are presented throughout to clarify the discussion.