Data-driven branching and selection for lot-sizing and scheduling problems with sequence-dependent setups and setup carryover

•A Dantzig-Wolfe formulation by machine decomposition is constructed.•A set-oriented data-driven branching and selection algorithm is proposed.•Numerical experiments justify the incorporation of the statistical estimation model. The capacitated lot-sizing and machine scheduling problem with sequence...

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Vydáno v:	Computers & operations research Ročník 132; s. 105289
Hlavní autoři:	Zhang, Canrong, Zhang, Dandan, Wu, Tao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Elsevier Ltd 01.08.2021 Pergamon Press Inc
Témata:	Algorithms Branching and selection Column generation Dantzig-Wolfe decomposition Data-driven Feature extraction Integer programming Job shops Linear programming Lot sizing Lower bounds Mathematical models Mixed integer Operations research Parallel machine scheduling Scheduling Lot-sizing Column generation Parallel machine scheduling Data-driven Branching and selection
ISSN:	0305-0548, 0305-0548
On-line přístup:	Získat plný text
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