A dynamic shipment matching problem in hinterland synchromodal transportation

Guo, Wenjing; Atasoy, Bilge; Blokland, Wouter Beelaerts van; Negenborn, Rudy R.

doi:10.1016/j.dss.2020.113289

Cited by 32 publications

(70 citation statements)

References 23 publications

(38 reference statements)

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“…Yee et al [29] presented a synchromodal decision support model based on the Markov decision process, and it allows adaptations to the modal choice based on real-time information on the travel time. Guo et al [30] proposed an online match platform between shipment requests and transportation services, and a rolling horizon approach and a heuristic algorithm were developed to handle the matching problems in hinterland synchromodal transportation dynamically. What's more, they also presented approaches with predictive information that perform better and proposed an anticipatory optimization approach for the matching problems [31].…”

Section: Innovation Logistics Conceptsmentioning

confidence: 99%

A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

Huang

Zhou

Xiong

et al. 2021

Journal of Advanced Transportation

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With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

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Section: Innovation Logistics Conceptsmentioning

confidence: 99%

A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

Huang

Zhou

Xiong

et al. 2021

Journal of Advanced Transportation

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“…Wiegmans and Konings (2015) and Seo et al (2017) 2 Meers et al (2018), Maras (2011), Konings (2006), Konings et al (2010), Konings and Priemus (2008), Guo et al (2020), Ramaekers et al (2017), Jourquin et al (2014), and Kotowska et al (2018) 13 Konings and Maras (2011), Konings (2006), Konings et al (2010), Konings and Priemus (2008), Grobarcikova and Sosedova (2016), Notteboom et al (2020), Notteboom (2007), Guo et al (2020), Kotowska et al (2018), Yang et al (2021), Balster et al (2020), Kemme (2012), andWagener (2014) 13 10 France Zehendner and Feillet (2014),…”

Section: Asian Journal Of Shipping and Logisticsmentioning

confidence: 99%

“…transportation network designLi et al (2015),Zehendner and Feillet (2014),Rajkovic et al (2016),Li et al (2014),Corman et al (2017),Grobarcikova and Sosedova (2016),Hann et al (2016),Kelleher et al (2003),Fremont and Franc (2010),Liu et al (2017),Clott et al (2015),Caris et al (2012),Guo et al (2020), Yahalom et al (2020), Bouchery et al (2020), Wagener (2014), Radmilovic et al (2011), Bai et al (2017), Nasir et al (2019), Tan et al (2018), Veenstra et al (2012), and Ambra et al (2019) 22 16 Empty container repositioning by barge Choong et al (2002), Braekers et al (2013), Roso et al (2015), Alfandari et al (2019), Maras (2008), Kolar et al (2018), Zhang et al (2020), and Wadhwa et al (2019) 8 Intermodal facility location Teye et al (2017), Lin et al (2014), Dotoli et al (2017), and Monios and Wilmsmeier container movement Mishra et al (2017), Gharehgozli et al (2017), Hu et al (2018), and Heilig and Voss (2017) 4 Port congestion management Meers et al (2018), Gumuskaya et al (2020a, b), and Zweers et al operation Vis and De Koster (2003), Dulebenets et al (2015), Konings and Priemus (2008), Nur et al (2020), Smid et al (2016), Cochrane (2008), Lopez-Plata et al (2018), Schepler et al (2017), Zhao et al (2018), Yu et al (2018), Park et al (2009), Zhang et al (2017), Zehendner et al (2015), Lee et al (2006), Musso and Sciomachen (2020), Kumawat et al (2021), and Zhen (2014) 17 13 Barge information sharing Zuidwijk and Veenstra (2015), Zhang et al (2016), and Fanti et al ), Ursavas and Zhu (2016), and Hansen et al relationships Duinkerken et al (2006), Castelein et al (2019) and van der Horst et al (2019Shobayo and van Hassel (2019), Douma et al (2011a, b), Konings and Maras (2011), Konings (2006), Konings et al (2013), Caris et al (2011), Konings (2007), Gracia et al (2019), Douma et al (2011a, b), Douma et al (2012), Feng et al (2015), Fu et al (2010), Lee et al (2014a, b), and Kemme (2012) 14 10 Barge capacity optimization Zweers et al (2019), Scherbina et al (2019), and Ramaekers et al strategies for COB developm...…”

mentioning

confidence: 99%

“…(2018),Fazi and Roodbergen (2018),Guo et al (2020),Fazi et al (2020),Hansen et al (2008), Lopez-Plata et al (2018,Zhang et al (2017),Infante et al (2009), Zhen (. (2020),Notteboom (2007),Konings (2007), Bomba and Harrison (2002), Konings et al (2010), Yang et al (2021), Santos and Soares (2017), and Kaack et al Koster (2003), Konings and Priemus (2008), Kolar et al (2018), Macharis and Bontekoning (2004), Heilig and Voss (2017), Monios and Wilmsmeier (2013), and Ambra et al .…”

mentioning

confidence: 99%

See 1 more Smart Citation

Literature review and comparative analysis of inland waterways transport: “Container on Barge”

Fan

Nachtmann

2021

Marit Econ Logist

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Container on Barge (COB) facilitates intermodal transportation by transporting shipping containers on barge tows. COB has seen rapid expansion globally over the past 20 years, providing a cost-efficient, environmentally friendly, and congestion-reducing mode of container transportation. European countries have led COB transportation in both study and application over the past two decades. However, increasing interest is observed in both the USA and Asia. In this literature review and comparative analysis, 135 COB-focused peer-reviewed articles are reviewed and analyzed to systematically describe the development and current status of COB transportation research. The relevant literature is analyzed to reveal publication rates and titles, geographical regions of interest, research questions, applied methodologies, advantages of COB transportation, and key success factors. The aim of our effort is to provide information on various aspects of COB development among different regions in the world and to summarize the existing literature to support and guide future COB development.

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“…In practice, container transport companies receive shipment requests from both long-term contracts and spot markets (Meng et al 2019). Different from the contractual requests received from large shippers whose information is known before the operational planning horizon, the information of spot requests is unknown and revealed dynamically (Guo et al 2020). The demand from the spot market is influenced by many factors, such as global economy, seasonality, fluctuations of freight rate, and competitions from other companies (Wang and Meng 2021).…”

Section: Introductionmentioning

confidence: 99%

Anticipatory approach for dynamic and stochastic shipment matching in hinterland synchromodal transportation

et al. 2021

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This paper investigates a dynamic and stochastic shipment matching problem faced by network operators in hinterland synchromodal transportation. We consider a platform that receives contractual and spot shipment requests from shippers, and receives multimodal services from carriers. The platform aims to provide optimal matches between shipment requests and multimodal services within a finite horizon under spot request uncertainty. Due to the capacity limitation of multimodal services, the matching decisions made for current requests will affect the ability to make good matches for future requests. To solve the problem, this paper proposes an anticipatory approach which consists of a rolling horizon framework that handles dynamic events, a sample average approximation method that addresses uncertainties, and a progressive hedging algorithm that generates solutions at each decision epoch. Compared with the greedy approach which is commonly used in practice, the anticipatory approach has total cost savings up to 8.18% under realistic instances. The experimental results highlight the benefits of incorporating stochastic information in dynamic decision making processes of the synchromodal matching system.

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A dynamic shipment matching problem in hinterland synchromodal transportation

Cited by 32 publications

References 23 publications

A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

Literature review and comparative analysis of inland waterways transport: “Container on Barge”

Anticipatory approach for dynamic and stochastic shipment matching in hinterland synchromodal transportation

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