Dynamic programming algorithms and Lagrangian lower bounds for a discrete lot streaming problem in a two-machine flow shop

In this paper, we propose exact and heuristic solution approaches based on dynamic programming for an open lot streaming problem. We also present the first application of Lagrangian relaxation to compute strong lower bounds to such a problem. The application concerns the minimization of the total fl...

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Veröffentlicht in:4OR Jg. 19; H. 2; S. 265 - 288
Hauptverfasser: Alfieri, Arianna, Zhou, Shuyu, Scatamacchia, Rosario, van de Velde, Steef L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021
Springer Nature B.V
Schlagworte:
Algorithms
Business and Management
Dynamic programming
Heuristic
Industrial and Production Engineering
Integer programming
Lower bounds
Manufacturing
Operations research
Operations Research/Decision Theory
Optimization
Research Paper
Total flow time
Lagrangian relaxation
Setup times
90-08
90B35
Lot streaming
90C39
Flow shop
Dynamic programming
ISSN:1619-4500, 1614-2411
Online-Zugang:Volltext
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Zusammenfassung:In this paper, we propose exact and heuristic solution approaches based on dynamic programming for an open lot streaming problem. We also present the first application of Lagrangian relaxation to compute strong lower bounds to such a problem. The application concerns the minimization of the total flow time for the discrete version of a single-job lot streaming problem from the literature in a two-machine flow shop with attached setup times. Computational results on benchmark instances illustrate the effectiveness of the proposed approaches and give evidence of the strength of the Lagrangian relaxation lower bounds.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-020-00449-8