Scheduling controllable processing time jobs with position-dependent workloads
In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Oron, Daniel [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation - 2013, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:173 ; year:2016 ; pages:153-160 ; extent:8 |
| Links: |
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| DOI / URN: |
10.1016/j.ijpe.2015.12.014 |
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ELV029883962 |
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| 520 | |a In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. | ||
| 520 | |a In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. | ||
| 650 | 7 | |a Resource consumption function |2 Elsevier | |
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| 650 | 7 | |a Total flowtime |2 Elsevier | |
| 650 | 7 | |a Workload |2 Elsevier | |
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10.1016/j.ijpe.2015.12.014 doi GBVA2016015000025.pica (DE-627)ELV029883962 (ELSEVIER)S0925-5273(15)00539-3 DE-627 ger DE-627 rakwb eng 330 330 DE-600 540 VZ 540 VZ 35.10 bkl Oron, Daniel verfasserin aut Scheduling controllable processing time jobs with position-dependent workloads 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. Resource consumption function Elsevier Makespan Elsevier Total flowtime Elsevier Workload Elsevier Enthalten in Elsevier Science TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation 2013 Amsterdam [u.a.] (DE-627)ELV016982673 volume:173 year:2016 pages:153-160 extent:8 https://doi.org/10.1016/j.ijpe.2015.12.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_23 GBV_ILN_70 35.10 Physikalische Chemie: Allgemeines VZ AR 173 2016 153-160 8 045F 330 |
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10.1016/j.ijpe.2015.12.014 doi GBVA2016015000025.pica (DE-627)ELV029883962 (ELSEVIER)S0925-5273(15)00539-3 DE-627 ger DE-627 rakwb eng 330 330 DE-600 540 VZ 540 VZ 35.10 bkl Oron, Daniel verfasserin aut Scheduling controllable processing time jobs with position-dependent workloads 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. Resource consumption function Elsevier Makespan Elsevier Total flowtime Elsevier Workload Elsevier Enthalten in Elsevier Science TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation 2013 Amsterdam [u.a.] (DE-627)ELV016982673 volume:173 year:2016 pages:153-160 extent:8 https://doi.org/10.1016/j.ijpe.2015.12.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_23 GBV_ILN_70 35.10 Physikalische Chemie: Allgemeines VZ AR 173 2016 153-160 8 045F 330 |
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10.1016/j.ijpe.2015.12.014 doi GBVA2016015000025.pica (DE-627)ELV029883962 (ELSEVIER)S0925-5273(15)00539-3 DE-627 ger DE-627 rakwb eng 330 330 DE-600 540 VZ 540 VZ 35.10 bkl Oron, Daniel verfasserin aut Scheduling controllable processing time jobs with position-dependent workloads 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. Resource consumption function Elsevier Makespan Elsevier Total flowtime Elsevier Workload Elsevier Enthalten in Elsevier Science TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation 2013 Amsterdam [u.a.] (DE-627)ELV016982673 volume:173 year:2016 pages:153-160 extent:8 https://doi.org/10.1016/j.ijpe.2015.12.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_23 GBV_ILN_70 35.10 Physikalische Chemie: Allgemeines VZ AR 173 2016 153-160 8 045F 330 |
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10.1016/j.ijpe.2015.12.014 doi GBVA2016015000025.pica (DE-627)ELV029883962 (ELSEVIER)S0925-5273(15)00539-3 DE-627 ger DE-627 rakwb eng 330 330 DE-600 540 VZ 540 VZ 35.10 bkl Oron, Daniel verfasserin aut Scheduling controllable processing time jobs with position-dependent workloads 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. Resource consumption function Elsevier Makespan Elsevier Total flowtime Elsevier Workload Elsevier Enthalten in Elsevier Science TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation 2013 Amsterdam [u.a.] (DE-627)ELV016982673 volume:173 year:2016 pages:153-160 extent:8 https://doi.org/10.1016/j.ijpe.2015.12.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_23 GBV_ILN_70 35.10 Physikalische Chemie: Allgemeines VZ AR 173 2016 153-160 8 045F 330 |
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10.1016/j.ijpe.2015.12.014 doi GBVA2016015000025.pica (DE-627)ELV029883962 (ELSEVIER)S0925-5273(15)00539-3 DE-627 ger DE-627 rakwb eng 330 330 DE-600 540 VZ 540 VZ 35.10 bkl Oron, Daniel verfasserin aut Scheduling controllable processing time jobs with position-dependent workloads 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. Resource consumption function Elsevier Makespan Elsevier Total flowtime Elsevier Workload Elsevier Enthalten in Elsevier Science TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation 2013 Amsterdam [u.a.] (DE-627)ELV016982673 volume:173 year:2016 pages:153-160 extent:8 https://doi.org/10.1016/j.ijpe.2015.12.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_23 GBV_ILN_70 35.10 Physikalische Chemie: Allgemeines VZ AR 173 2016 153-160 8 045F 330 |
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Enthalten in TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation Amsterdam [u.a.] volume:173 year:2016 pages:153-160 extent:8 |
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Enthalten in TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation Amsterdam [u.a.] volume:173 year:2016 pages:153-160 extent:8 |
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TiO2 nanoparticle assisted solid phase photocatalytic degradation of polythene film: A mechanistic investigation |
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In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. |
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In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. |
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In various real life applications job processing times are controllable through the allocation of a limited resource. To date research has been conducted under the assumption that the relationship between the amount of resource allocated to a job and its processing time is independent of the number of tasks processed previously. However, there exist many manufacturing and service systems where workers and machines acquire, develop and refine skills through the repetition of identical or similar operations. In this paper we consider a scheduling model where job processing times are a convex function of the amount of resource they are allocated. In addition, we assume that the parameters of this function are position-dependent, i.e., vary with the job׳s position in the sequence. This assumption reflects general processes of learning or aging, or a combination of both. We first focus on a single machine setting and the makespan and total flowtime criteria. We show that the combined problem of finding an optimal job sequence and an optimal resource allocation can be solved in O ( n 3 ) time. We show that our algorithm can be used to address a bicriteria objective comprising of a linear combination of makespan and the total flowtime criteria on a single machine. We then extend the results to a parallel machine setting for the total flowtime criteria. |
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