A best possible on-line algorithm for two-machine flow shop scheduling to minimize makespan

We address a two-machine flow shop on-line scheduling problem. Jobs arrive over time. Each job becomes available for processing at its release time after which it must be processed without preemption on the first machine and then on the second machine. The objective is to minimize the makespan. We p...

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Veröffentlicht in:Computers & operations research Jg. 51; S. 251 - 256
Hauptverfasser: Liu, Peihai, Lu, Xiwen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.11.2014
Elsevier
Pergamon Press Inc
Schlagworte:
Algorithms
Applied sciences
Competitive ratio
Exact sciences and technology
Flow shop
Inventory control, production control. Distribution
Job shops
Mathematical problems
Online
Operational research and scientific management
Operational research. Management science
Operations research
Optimization algorithms
Production scheduling
Scheduling
Scheduling algorithms
Scheduling, sequencing
Studies
Scheduling
Flow shop
Competitive ratio
Online
Preemption
On line
Multiple machine
Priority
Competitiveness
Processing time
Makespan
Competitive algorithms
Production management
Deterministic algorithms
Execution time
ISSN:0305-0548, 1873-765X, 0305-0548
Online-Zugang:Volltext
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Zusammenfassung:We address a two-machine flow shop on-line scheduling problem. Jobs arrive over time. Each job becomes available for processing at its release time after which it must be processed without preemption on the first machine and then on the second machine. The objective is to minimize the makespan. We provide a best possible deterministic on-line algorithm with a competitive ratio of (5+1)/2. Computational experiments on randomly generated problem instances are performed and the results show that the online algorithm is very useful to obtain near-optimal solutions.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2014.06.014