Robust load planning of trains in intermodal transportation
Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation cost...
Ausführliche Beschreibung
Autor*in: |
Bruns, Florian [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2013 |
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Schlagwörter: |
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Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2013 |
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Übergeordnetes Werk: |
Enthalten in: OR spectrum - Springer Berlin Heidelberg, 2002, 36(2013), 3 vom: 06. Sept., Seite 631-668 |
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Übergeordnetes Werk: |
volume:36 ; year:2013 ; number:3 ; day:06 ; month:09 ; pages:631-668 |
Links: |
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DOI / URN: |
10.1007/s00291-013-0341-8 |
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Katalog-ID: |
OLC2091993778 |
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520 | |a Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. | ||
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700 | 1 | |a Schöbel, Anita |4 aut | |
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10.1007/s00291-013-0341-8 doi (DE-627)OLC2091993778 (DE-He213)s00291-013-0341-8-p DE-627 ger DE-627 rakwb eng 650 VZ 650 VZ 3,2 ssgn Bruns, Florian verfasserin aut Robust load planning of trains in intermodal transportation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. Load planning Intermodal transportation Robustness Strict robustness Adjustable robustness Goerigk, Marc aut Knust, Sigrid aut Schöbel, Anita aut Enthalten in OR spectrum Springer Berlin Heidelberg, 2002 36(2013), 3 vom: 06. Sept., Seite 631-668 (DE-627)343968762 (DE-600)2073885-7 (DE-576)097935891 0171-6468 nnns volume:36 year:2013 number:3 day:06 month:09 pages:631-668 https://doi.org/10.1007/s00291-013-0341-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW GBV_ILN_20 GBV_ILN_22 GBV_ILN_26 GBV_ILN_30 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_130 GBV_ILN_132 GBV_ILN_185 GBV_ILN_358 GBV_ILN_673 GBV_ILN_2012 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4318 GBV_ILN_4323 GBV_ILN_4333 AR 36 2013 3 06 09 631-668 |
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10.1007/s00291-013-0341-8 doi (DE-627)OLC2091993778 (DE-He213)s00291-013-0341-8-p DE-627 ger DE-627 rakwb eng 650 VZ 650 VZ 3,2 ssgn Bruns, Florian verfasserin aut Robust load planning of trains in intermodal transportation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. Load planning Intermodal transportation Robustness Strict robustness Adjustable robustness Goerigk, Marc aut Knust, Sigrid aut Schöbel, Anita aut Enthalten in OR spectrum Springer Berlin Heidelberg, 2002 36(2013), 3 vom: 06. Sept., Seite 631-668 (DE-627)343968762 (DE-600)2073885-7 (DE-576)097935891 0171-6468 nnns volume:36 year:2013 number:3 day:06 month:09 pages:631-668 https://doi.org/10.1007/s00291-013-0341-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW GBV_ILN_20 GBV_ILN_22 GBV_ILN_26 GBV_ILN_30 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_130 GBV_ILN_132 GBV_ILN_185 GBV_ILN_358 GBV_ILN_673 GBV_ILN_2012 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4318 GBV_ILN_4323 GBV_ILN_4333 AR 36 2013 3 06 09 631-668 |
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10.1007/s00291-013-0341-8 doi (DE-627)OLC2091993778 (DE-He213)s00291-013-0341-8-p DE-627 ger DE-627 rakwb eng 650 VZ 650 VZ 3,2 ssgn Bruns, Florian verfasserin aut Robust load planning of trains in intermodal transportation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. Load planning Intermodal transportation Robustness Strict robustness Adjustable robustness Goerigk, Marc aut Knust, Sigrid aut Schöbel, Anita aut Enthalten in OR spectrum Springer Berlin Heidelberg, 2002 36(2013), 3 vom: 06. Sept., Seite 631-668 (DE-627)343968762 (DE-600)2073885-7 (DE-576)097935891 0171-6468 nnns volume:36 year:2013 number:3 day:06 month:09 pages:631-668 https://doi.org/10.1007/s00291-013-0341-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW GBV_ILN_20 GBV_ILN_22 GBV_ILN_26 GBV_ILN_30 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_130 GBV_ILN_132 GBV_ILN_185 GBV_ILN_358 GBV_ILN_673 GBV_ILN_2012 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4318 GBV_ILN_4323 GBV_ILN_4333 AR 36 2013 3 06 09 631-668 |
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10.1007/s00291-013-0341-8 doi (DE-627)OLC2091993778 (DE-He213)s00291-013-0341-8-p DE-627 ger DE-627 rakwb eng 650 VZ 650 VZ 3,2 ssgn Bruns, Florian verfasserin aut Robust load planning of trains in intermodal transportation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. Load planning Intermodal transportation Robustness Strict robustness Adjustable robustness Goerigk, Marc aut Knust, Sigrid aut Schöbel, Anita aut Enthalten in OR spectrum Springer Berlin Heidelberg, 2002 36(2013), 3 vom: 06. Sept., Seite 631-668 (DE-627)343968762 (DE-600)2073885-7 (DE-576)097935891 0171-6468 nnns volume:36 year:2013 number:3 day:06 month:09 pages:631-668 https://doi.org/10.1007/s00291-013-0341-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW GBV_ILN_20 GBV_ILN_22 GBV_ILN_26 GBV_ILN_30 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_130 GBV_ILN_132 GBV_ILN_185 GBV_ILN_358 GBV_ILN_673 GBV_ILN_2012 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4318 GBV_ILN_4323 GBV_ILN_4333 AR 36 2013 3 06 09 631-668 |
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10.1007/s00291-013-0341-8 doi (DE-627)OLC2091993778 (DE-He213)s00291-013-0341-8-p DE-627 ger DE-627 rakwb eng 650 VZ 650 VZ 3,2 ssgn Bruns, Florian verfasserin aut Robust load planning of trains in intermodal transportation 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2013 Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. Load planning Intermodal transportation Robustness Strict robustness Adjustable robustness Goerigk, Marc aut Knust, Sigrid aut Schöbel, Anita aut Enthalten in OR spectrum Springer Berlin Heidelberg, 2002 36(2013), 3 vom: 06. Sept., Seite 631-668 (DE-627)343968762 (DE-600)2073885-7 (DE-576)097935891 0171-6468 nnns volume:36 year:2013 number:3 day:06 month:09 pages:631-668 https://doi.org/10.1007/s00291-013-0341-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW GBV_ILN_20 GBV_ILN_22 GBV_ILN_26 GBV_ILN_30 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_110 GBV_ILN_130 GBV_ILN_132 GBV_ILN_185 GBV_ILN_358 GBV_ILN_673 GBV_ILN_2012 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4247 GBV_ILN_4277 GBV_ILN_4318 GBV_ILN_4323 GBV_ILN_4333 AR 36 2013 3 06 09 631-668 |
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Enthalten in OR spectrum 36(2013), 3 vom: 06. Sept., Seite 631-668 volume:36 year:2013 number:3 day:06 month:09 pages:631-668 |
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Enthalten in OR spectrum 36(2013), 3 vom: 06. Sept., Seite 631-668 volume:36 year:2013 number:3 day:06 month:09 pages:631-668 |
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Bruns, Florian @@aut@@ Goerigk, Marc @@aut@@ Knust, Sigrid @@aut@@ Schöbel, Anita @@aut@@ |
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Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. © Springer-Verlag Berlin Heidelberg 2013 |
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Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. © Springer-Verlag Berlin Heidelberg 2013 |
abstract_unstemmed |
Abstract In this paper, the problem of robust load planning for trains in intermodal container terminals is studied. The goal of load planning is to choose wagon settings and assign load units to wagons of a train such that the utilization of the train is maximized, and setup and transportation costs in the terminal are minimized. However, in real-world applications, many of the parameters needed for the model are not known exactly. Since feasibility of the resulting load distribution has always to be guaranteed, we decided to use a robust approach. In particular, we apply the concepts of strict and adjustable robustness to enhance the load planning problem. Based on a formulation developed in Bruns and Knust (OR Spectrum 34:511–533, 2012) for the deterministic load planning problem, we propose mixed-integer linear programming formulations for most of the respective robust counterparts, dependent on the type of uncertainty. An experimental study shows that most of the robust problems can be solved within runtimes of a few minutes, which is good enough for real-world applications. Furthermore, our results indicate that robust solutions may improve the planning considerably, and that it is promising to add robustness even to large mixed-integer programs with many and diverse technical constraints. © Springer-Verlag Berlin Heidelberg 2013 |
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