Abstract
With the increasing volumes of containers in global trade, efficient global container transport planning becomes more and more important. To improve the competitiveness in global supply chains, stakeholders turn to collaborate with each other at vertical as well as horizontal level, namely synchromodal transportation. Synchromodality is the provision of efficient, effective, and sustainable transport plans for all the shipments involved in an integrated network driven by advanced information technologies. However, the decision-making processes of a global synchromodal transport system is very complex. First, time-dependent travel times caused by traffic congestion need to be considered. Second, a dynamic approach that handles real-time shipment requests in a synchromodal network is required. Third, spot requests received from spot markets are unknown in advance. Fourth, travel time uncertainty is not handled yet for global synchromodal transport networks. Fifth, distributed approaches that stimulate cooperation among multiple stakeholders involved in global container transportation are still missing. This thesis addresses the above-mentioned challenges with dynamic, stochastic, and coordinated models.
| Original language | English |
|---|---|
| Qualification | Doctor of Philosophy |
| Awarding Institution |
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| Supervisors/Advisors |
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| Thesis sponsors |
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| Award date | 13 Nov 2020 |
| Publisher |
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| Print ISBNs | 979-90-5584-273-5 |
| DOIs | |
| Publication status | Published - 2020 |
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Guo, W. (2020). Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms. [Dissertation (TU Delft), Delft University of Technology]. TRAIL Research School. https://doi.org/10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0
Guo, W.. / Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms. TRAIL Research School, 2020. 174 p.
@phdthesis{6806500b6ed94d94a4d717965cfc9ca0,
title = "Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms",
abstract = "With the increasing volumes of containers in global trade, efficient global container transport planning becomes more and more important. To improve the competitiveness in global supply chains, stakeholders turn to collaborate with each other at vertical as well as horizontal level, namely synchromodal transportation. Synchromodality is the provision of efficient, effective, and sustainable transport plans for all the shipments involved in an integrated network driven by advanced information technologies. However, the decision-making processes of a global synchromodal transport system is very complex. First, time-dependent travel times caused by traffic congestion need to be considered. Second, a dynamic approach that handles real-time shipment requests in a synchromodal network is required. Third, spot requests received from spot markets are unknown in advance. Fourth, travel time uncertainty is not handled yet for global synchromodal transport networks. Fifth, distributed approaches that stimulate cooperation among multiple stakeholders involved in global container transportation are still missing. This thesis addresses the above-mentioned challenges with dynamic, stochastic, and coordinated models.",
author = "W. Guo",
year = "2020",
doi = "10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0",
language = "English",
isbn = "979-90-5584-273-5",
series = "TRAIL Thesis Series T2020/16",
publisher = "TRAIL Research School",
type = "Dissertation (TU Delft)",
school = "Delft University of Technology",
}
Guo, W 2020, 'Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms', Doctor of Philosophy, Delft University of Technology. https://doi.org/10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0
Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms. / Guo, W.
TRAIL Research School, 2020. 174 p.
Research output: Thesis › Dissertation (TU Delft)
TY - THES
T1 - Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms
AU - Guo, W.
PY - 2020
Y1 - 2020
N2 - With the increasing volumes of containers in global trade, efficient global container transport planning becomes more and more important. To improve the competitiveness in global supply chains, stakeholders turn to collaborate with each other at vertical as well as horizontal level, namely synchromodal transportation. Synchromodality is the provision of efficient, effective, and sustainable transport plans for all the shipments involved in an integrated network driven by advanced information technologies. However, the decision-making processes of a global synchromodal transport system is very complex. First, time-dependent travel times caused by traffic congestion need to be considered. Second, a dynamic approach that handles real-time shipment requests in a synchromodal network is required. Third, spot requests received from spot markets are unknown in advance. Fourth, travel time uncertainty is not handled yet for global synchromodal transport networks. Fifth, distributed approaches that stimulate cooperation among multiple stakeholders involved in global container transportation are still missing. This thesis addresses the above-mentioned challenges with dynamic, stochastic, and coordinated models.
AB - With the increasing volumes of containers in global trade, efficient global container transport planning becomes more and more important. To improve the competitiveness in global supply chains, stakeholders turn to collaborate with each other at vertical as well as horizontal level, namely synchromodal transportation. Synchromodality is the provision of efficient, effective, and sustainable transport plans for all the shipments involved in an integrated network driven by advanced information technologies. However, the decision-making processes of a global synchromodal transport system is very complex. First, time-dependent travel times caused by traffic congestion need to be considered. Second, a dynamic approach that handles real-time shipment requests in a synchromodal network is required. Third, spot requests received from spot markets are unknown in advance. Fourth, travel time uncertainty is not handled yet for global synchromodal transport networks. Fifth, distributed approaches that stimulate cooperation among multiple stakeholders involved in global container transportation are still missing. This thesis addresses the above-mentioned challenges with dynamic, stochastic, and coordinated models.
U2 - 10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0
DO - 10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0
M3 - Dissertation (TU Delft)
SN - 979-90-5584-273-5
T3 - TRAIL Thesis Series T2020/16
PB - TRAIL Research School
ER -
Guo W. Dynamic, Stochastic, and Coordinated Optimization for Synchromodal Matching Platforms. TRAIL Research School, 2020. 174 p. (TRAIL Thesis Series T2020/16). doi: 10.4233/uuid:6806500b-6ed9-4d94-a4d7-17965cfc9ca0
