Disruption Management for Liner Shipping

Qi, Xinyuan

doi:10.1007/978-3-319-11891-8_8

Cited by 17 publications

(8 citation statements)

References 29 publications

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“…In this field, empirical approaches using a network-based approach mainly deployed simulation models to measure how unpredicted shocks threaten network efficiency (see Asadabadi and Miller-Hooks, 2018;Burden et al, 2016;Mullai and Paulsson, 2011;Omer et al, 2012;Shafieezadeh and Ivey Burden, 2014). In addition, some authors studied port resilience in the face of disruptions and liner shipping coping with such events (Shaw et al, 2017;Achurra-Gonzalez et al, 2017;Qi, 2015).…”

Section: Research Background and Objectivesmentioning

confidence: 99%

Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns

Rousset

Ducruet

2019

Netw Spat Econ

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In this research, the effect of local exogenous shocks on seaports and maritime networks is assessed throughout three case-studies. The Hanshin-Awaji earthquake, the 9/11 World Trade Center attack and hurricane Katrina triggered a shock on Kobe, New York and New Orleans respectively and led to temporary port failures. A global database on vessel movements is computed to gauge the intensity, duration and scope of these shocks with descriptive statistics. Port-centered analyses of the disrupted ports and their geographic as well as topological neighbors are conducted to assess the resilience of local port systems using traffic volumes, distances, and graph-theoretical methods at various time scales, from daily to yearly evolutions. Main results demonstrate certain similarities between the three cases given the importance of traffic specialization and of the spatial range of disruption.

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Section: Research Background and Objectivesmentioning

confidence: 99%

Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns

Rousset

Ducruet

2019

Netw Spat Econ

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“…Previous studies have focused on the study of maritime supply chains risk with a focus on port disruptions (e.g. Lam, 2012;Loh and Van Thai, 2014;Mansouri et al, 2010;Qi, 2015). However, this initial non-exhaustive taxonomy is, to the best of our knowledge, the first attempt to classify perturbations that impact additional liner shipping network components beyond ports as focal point such as route capacity and factors influencing origins and destinations of containerised cargo.…”

Section: Classification Scheme For Liner Shipping Network Perturbationsmentioning

confidence: 99%

“…Previous works have discussed the impact of port disruptions from risk sources other than natural disasters and political conflicts including labour strikes, equipment failure, human errors and terrorist attacks (Lam and Yip, 2012;Lewis et al, 2013;Mansouri et al, 2010). Table 2.1 includes a list of various examples of port disruptions that occurred between January 2012 and January 2014 (Qi, 2015) in order to illustrate the vulnerability of the liner shipping industry to these events. For comprehensive reviews of port-centric disruptions affecting maritime supply chains we refer to Lam (2012) and Loh and Van Thai (2014).…”

Section: Classification Scheme For Liner Shipping Network Perturbationsmentioning

confidence: 99%

Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Achurra-Gonzalez

Novati²,

Foulser‐Piggott

et al. 2019

Accident Analysis & Prevention

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Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity.

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“…• Delay in logistics service provider selection ( Qi, 2015 ). Some companies consider stepwise value function for delay in delivering the items by a logistics service provider, which means that the value of that provider decreases when delay increases, however it is constant within certain intervals.…”

Section: Decreasing Stepwisementioning

confidence: 99%

Piecewise linear value functions for multi-criteria decision-making

Rezaei

2018

Expert Systems with Applications

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Multi-criteria decision-making (MCDM) concerns selecting, ranking or sorting a set of alternatives which are evaluated with respect to a number of criteria. There are several MCDM methods, the two core elements of which are (i) evaluating the performance of the alternatives with respect to the criteria, (ii) finding the importance (weight) of the criteria. There are several methods to find the weights of the criteria, however, when it comes to the alternative measures with respect to the criteria, usually the existing MCDM methods use simple monotonic linear value functions. Usually an increasing or decreasing linear function is assumed between a criterion level (over its entire range) and its value. This assumption, however, might lead to improper results. This study proposes a family of piecewise value functions which can be used for different decision criteria for different decision problems. Several real-world examples from existing literature are provided to illustrate the applicability of the proposed value functions. A numerical example of supplier selection (including a comparison between simple monotonic linear value functions, piecewise linear value functions, and exponential value functions) shows how considering proper value functions could affect the final results of an MCDM problem.

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Disruption Management for Liner Shipping

Cited by 17 publications

References 29 publications

Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns

Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns

Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Piecewise linear value functions for multi-criteria decision-making

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