Imperial College London


Faculty of EngineeringDepartment of Civil and Environmental Engineering

Honorary Research Fellow







609Skempton BuildingSouth Kensington Campus





Publication Type

8 results found

Goldbeck N, Angeloudis P, Ochieng W, 2020, Optimal supply chain resilience with consideration of failure propagation and repair logistics, Transportation Research Part E: Logistics and Transportation Review, Vol: 133, Pages: 1-20, ISSN: 1366-5545

The joint optimisation of investments in capacity and repair capability of production and logistics systems at risk of being damaged is an important aspect of supply chain resilience that is not sufficiently addressed by state-of-the-art modelling approaches. Furthermore, logistical issues of procuring repair resources impact speed of recovery but are not considered in most existing models. This paper presents a novel multi-stage stochastic programming model that optimizes pre-disruption investment decisions, as well as post-disruption dynamic adjustment of supply chain operations and allocation of repair resources. A case study demonstrates how the method can quantify the effects of pooling repair resources.

Journal article

Goldbeck N, Angeloudis P, Ochieng W, 2019, Resilience assessment for interdependent urban infrastructure systems using dynamic network flow models, Reliability Engineering and System Safety, Vol: 188, Pages: 62-79, ISSN: 0951-8320

Critical infrastructure systems are becoming increasingly interdependent, which can exacerbate the impacts of disruptive events through cascading failures, hindered asset repairs and network congestion. Current resilience assessment methods fall short of fully capturing such interdependency effects as they tend to model asset reliability and network flows separately and often rely on static flow assignment methods. In this paper, we develop an integrated, dynamic modelling and simulation framework that combines network and asset representations of infrastructure systems and models the optimal response to disruptions using a rolling planning horizon. The framework considers dependencies pertaining to failure propagation, system-of-systems architecture and resources required for operating and repairing assets. Stochastic asset failure is captured by a scenario tree generation algorithm whereas the redistribution of network flows and the optimal deployment of repair resources are modelled using a minimum cost flow approach. A case study on London’s metro and electric power networks shows how the proposed methodology can be used to assess the resilience of city-scale infrastructure systems to a local flooding incident and estimate the value of the resilience loss triangle for different levels of hazard exposure and repair capabilities.

Journal article

Achurra-Gonzalez PE, Angeloudis P, Goldbeck N, Graham D, Zavitsas K, Stettler Met al., 2019, Evaluation of port disruption impacts in the global liner shipping network, Journal of Shipping and Trade, Vol: 4, Pages: 1-21, ISSN: 2364-4575

The global container shipping network is vital to international trade. Current techniques for its vulnerability assessment are constrained due to the lack of historical disruption data and computational limitations due to typical network sizes. We address these modelling challenges by developing a new framework, composed by a game-theoretic attacker-defender model and a cost-based container assignment model that can identify systemic vulnerabilities in the network. Given its focus on logic and structure, the proposed framework has minimal input data requirements and does not rely on the presence of extensive historical disruption data. Numerical implementations are carried in a global-scale liner network where disruptions occur in Europe’s main container ports. Model outputs are used to establish performance baselines for the network and illus-trate the differences in regional vulnerability levels and port criticality rankings with different disruption magnitudes and flow diversion strategies. Sensitivity analysis of these outputs identifies network compo-nents that are more susceptible to lower levels of disruption which are more common in practice and to assess the effectiveness of component-level interventions seeking to increase the resilience of the system.

Journal article

Goldbeck N, Angeloudis P, Ochieng W, 2017, A Dynamic Network Flow Model for Interdependent Infrastructure and Supply Chain Networks with Uncertain Asset Operability, International Conference on Computational Logistics

Conference paper

Goldbeck N, Angeloudis P, 2017, Civil Engineering: Unlocking the potential of future cities through sustainable and resilient infrastructure, Defining the Urban: Interdisciplinary and Professional Perspectives, Editors: Iossifova, Gasparatos, Doll, Publisher: Routledge, ISBN: 978-1472449498

Book chapter

Goldbeck N, Angeloudis P, Ochieng W, 2016, Analysing the resilience of metro systems under consideration of interdependencies: A combined Dynamic Bayesian Network and network flow approach, 14th World Conference on Transport Research (WCTR)

Conference paper

Goldbeck N, Angeloudis P, Ochieng W, 2016, Joint Vulnerability Analysis of Urban Rail Transit and Utility Networks, Transportation Research Board 95th Annual Meeting, Publisher: Transportation Research Board

As climate change is expected to increase the frequency of extreme weather events, cities around the world develop strategies to improve their disaster resilience. A key issue is the protection of critical urban infrastructure systems, such as transport networks. Rail transit networks are particularly exposed to flood risks and additional vulnerabilities arise from interdependencies with other infrastructure systems. This paper aims to improve modelling techniques that help to understand the conditions under which cascading failure can occur in interdependent urban infrastructure systems. Building on existing network flow models, a novel method for the coupling of networks is introduced, using binary connector variables and mixed integer linear programming. The coupling is modelled as additional commodity demand that is induced in one network depending on the commodity flows in another network. An example problem consisting of a rail transit network, a control system, an electric power network and a water supply network illustrates the practicability of the proposed modelling technique.

Conference paper

Goldbeck N, Angeloudis P, Ochieng W, 2015, Analysis of cascading failures across interdependent dynamic networks, 27th European Conference on Operational Research

Conference paper

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