Near-linear-time approximation algorithms for scheduling a batch-processing machine with setups and job rejection

In this paper we study a single batch-processing machine scheduling model. In our model, a set of jobs having different release dates needs to be scheduled onto a single machine that can process a batch of jobs simultaneously at a time. Each batch incurs a fixed setup time and a fixed setup cost. Th...

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Veröffentlicht in:Journal of scheduling Jg. 23; H. 5; S. 525 - 538
1. Verfasser: Ou, Jinwen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.10.2020
Springer Nature B.V
Schlagworte:
Algorithms
Approximation
Artificial Intelligence
Batch processing
Business and Management
Calculus of Variations and Optimal Control; Optimization
Decision making
Mathematical analysis
Operations Research/Decision Theory
Optimization
Rejection
Release dates
Scheduling
Supply Chain Management
Scheduling
Performance analysis
Batch processing
Approximation algorithm
Job rejection
ISSN:1094-6136, 1099-1425
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Beschreibung
Zusammenfassung:In this paper we study a single batch-processing machine scheduling model. In our model, a set of jobs having different release dates needs to be scheduled onto a single machine that can process a batch of jobs simultaneously at a time. Each batch incurs a fixed setup time and a fixed setup cost. The decision maker may reject some of the jobs by paying penalty cost so as to achieve a tight makespan, but the total rejection penalty cost is required to be no greater than a given value. Our model extends several existing batch-processing machine scheduling models in the literature. We present efficient approximation algorithms with near-linear-time complexities.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1094-6136
1099-1425
DOI:10.1007/s10951-020-00657-4