Optimally rescheduling jobs with a Last-In-First-Out buffer

This paper considers single-machine scheduling problems in which a given solution, i.e., an ordered set of jobs, has to be improved as much as possible by re-sequencing the jobs. The need for rescheduling may arise in different contexts, e.g., due to changes in the job data or because of the local o...

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Bibliographic Details
Published in:Journal of scheduling Vol. 24; no. 6; pp. 663 - 680
Main Authors: Nicosia, Gaia, Pacifici, Andrea, Pferschy, Ulrich, Resch, Julia, Righini, Giovanni
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2021
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Buffers
Business and Management
Calculus of Variations and Optimal Control; Optimization
Completion time
Dynamic programming
Job shops
Lateness
Operations Research/Decision Theory
Optimization
Polynomials
Rescheduling
Supply Chain Management
Supply chains
Dynamic programming algorithms
Scheduling
Rescheduling
Supply chain sustainability
Sequence coordination
Complexity
ISSN:1094-6136, 1099-1425
Online Access:Get full text
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Summary:This paper considers single-machine scheduling problems in which a given solution, i.e., an ordered set of jobs, has to be improved as much as possible by re-sequencing the jobs. The need for rescheduling may arise in different contexts, e.g., due to changes in the job data or because of the local objective in a stage of a supply chain that is not aligned with the given sequence. A common production setting entails the movement of jobs (or parts) on a conveyor. This is reflected in our model by facilitating the re-sequencing of jobs via a buffer of limited capacity accessible by a LIFO policy. We consider the classical objective functions of total weighted completion time, maximum lateness and (weighted) number of late jobs and study their complexity. For three of these problems, we present strictly polynomial-time dynamic programming algorithms, while for the case of minimizing the weighted number of late jobs NP-hardness is proven and a pseudo-polynomial algorithm is given.
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ISSN:1094-6136
1099-1425
DOI:10.1007/s10951-021-00707-5