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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| Vydané v: | Journal of scheduling Ročník 24; číslo 6; s. 663 - 680 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York
Springer US
01.12.2021
Springer Nature B.V |
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| ISSN: | 1094-6136, 1099-1425 |
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| Abstract | 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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| AbstractList | 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. |
| Author | Nicosia, Gaia Righini, Giovanni Pferschy, Ulrich Pacifici, Andrea Resch, Julia |
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| CitedBy_id | crossref_primary_10_1016_j_cie_2023_109610 crossref_primary_10_1287_ijoc_2023_0038 crossref_primary_10_1007_s10951_022_00751_9 crossref_primary_10_1016_j_omega_2024_103114 |
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| ContentType | Journal Article |
| Copyright | The Author(s) 2021 The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| DOI | 10.1007/s10951-021-00707-5 |
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| SubjectTerms | 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 |
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| Title | Optimally rescheduling jobs with a Last-In-First-Out buffer |
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