Scheduling to maximize the weighted number of on-time jobs on parallel machines with bounded job-rejection
We study a scheduling problem on parallel identical machines, where the objective function is maximizing the weighted number of jobs completed exactly at their due-dates. The scheduler may reject a subset of the jobs, and the total permitted rejection cost is assumed to be bounded. Thus, when a deci...
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| Vydáno v: | Journal of scheduling Ročník 26; číslo 2; s. 193 - 207 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Springer US
01.04.2023
Springer Nature B.V |
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| ISSN: | 1094-6136, 1099-1425 |
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| Abstract | We study a scheduling problem on parallel identical machines, where the objective function is maximizing the weighted number of jobs completed exactly at their due-dates. The scheduler may reject a subset of the jobs, and the total permitted rejection cost is assumed to be bounded. Thus, when a decision has to be made regarding a certain job, the following options need to be considered: either (
i
) identify the set of machines on which the job can be scheduled on time, and assign the job to one of these machines, or (
ii
) reject the job (if possible), or (
iii
) delay the job. A pseudo-polynomial dynamic programming algorithm is introduced for this NP-hard problem. Medium size problems are solved in reasonable running times. We then study a different version of the problem, in which job-dependent due-windows are considered, and the job processing times are assumed to be identical. This version is proved to be NP-hard, and a pseudo-polynomial dynamic programming algorithm is introduced as well. Our numerical study indicates that medium size instances can be handled for this version. In addition, for both problems, an alternative solution procedure based on integer-linear-programming formulation is introduced. |
|---|---|
| AbstractList | We study a scheduling problem on parallel identical machines, where the objective function is maximizing the weighted number of jobs completed exactly at their due-dates. The scheduler may reject a subset of the jobs, and the total permitted rejection cost is assumed to be bounded. Thus, when a decision has to be made regarding a certain job, the following options need to be considered: either (i) identify the set of machines on which the job can be scheduled on time, and assign the job to one of these machines, or (ii) reject the job (if possible), or (iii) delay the job. A pseudo-polynomial dynamic programming algorithm is introduced for this NP-hard problem. Medium size problems are solved in reasonable running times. We then study a different version of the problem, in which job-dependent due-windows are considered, and the job processing times are assumed to be identical. This version is proved to be NP-hard, and a pseudo-polynomial dynamic programming algorithm is introduced as well. Our numerical study indicates that medium size instances can be handled for this version. In addition, for both problems, an alternative solution procedure based on integer-linear-programming formulation is introduced. We study a scheduling problem on parallel identical machines, where the objective function is maximizing the weighted number of jobs completed exactly at their due-dates. The scheduler may reject a subset of the jobs, and the total permitted rejection cost is assumed to be bounded. Thus, when a decision has to be made regarding a certain job, the following options need to be considered: either ( i ) identify the set of machines on which the job can be scheduled on time, and assign the job to one of these machines, or ( ii ) reject the job (if possible), or ( iii ) delay the job. A pseudo-polynomial dynamic programming algorithm is introduced for this NP-hard problem. Medium size problems are solved in reasonable running times. We then study a different version of the problem, in which job-dependent due-windows are considered, and the job processing times are assumed to be identical. This version is proved to be NP-hard, and a pseudo-polynomial dynamic programming algorithm is introduced as well. Our numerical study indicates that medium size instances can be handled for this version. In addition, for both problems, an alternative solution procedure based on integer-linear-programming formulation is introduced. |
| Author | Mosheiov, Gur Atsmony, Matan |
| Author_xml | – sequence: 1 givenname: Matan surname: Atsmony fullname: Atsmony, Matan email: matan.atsmony@mail.huji.ac.il organization: School of Business Administration, The Hebrew University – sequence: 2 givenname: Gur surname: Mosheiov fullname: Mosheiov, Gur organization: School of Business Administration, The Hebrew University |
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| CitedBy_id | crossref_primary_10_1007_s10878_023_01074_x crossref_primary_10_1007_s10844_025_00940_w crossref_primary_10_46465_endustrimuhendisligi_1601313 crossref_primary_10_1016_j_cor_2025_107046 crossref_primary_10_1080_10556788_2024_2349091 crossref_primary_10_1080_00207543_2024_2314714 |
| Cites_doi | 10.1007/s10288-020-00436-z 10.1016/j.ipl.2017.12.004 10.1007/s10951-007-0030-z 10.1016/j.omega.2015.09.010 10.1007/s10479-018-2779-1 10.1007/s10951-018-0584-y 10.1080/00207543.2016.1266055 10.1080/01605682.2018.1506540 10.1016/j.ipl.2014.09.004 10.1080/00207543.2020.1727042 10.1007/s10951-010-0204-y 10.1007/s10951-017-0511-7 10.1016/0305-0548(95)00078-X 10.1007/s10951-012-0303-z 10.1007/s10951-013-0327-z 10.1007/978-981-15-3528-4_3 10.1504/IJSOM.2019.097527 10.1007/s40314-020-1130-z 10.1007/s10878-016-0044-6 10.1007/978-1-4614-1123-9_1 10.1080/01605682.2019.1621222 10.1007/s10951-005-2863-7 10.1051/ro/2017040 10.1080/0305215X.2020.1735380 10.1007/BF00121680 10.1016/S0305-0548(00)00086-1 10.1016/j.ipl.2019.02.008 |
| ContentType | Journal Article |
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| Keywords | Scheduling Job-rejection Dynamic programming Just-in-time Parallel identical machines |
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| SubjectTerms | Algorithms Artificial Intelligence Business and Management Calculus of Variations and Optimal Control; Optimization Dynamic programming Operations Research/Decision Theory Optimization Polynomials Rejection Run time (computers) Scheduling Supply Chain Management |
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| Title | Scheduling to maximize the weighted number of on-time jobs on parallel machines with bounded job-rejection |
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