Mitigating transportation disruptions in the Australian household hydrogen supply chain

Pranto CHAKRABARTY , Sanjoy Kumar PAUL , Andrea TRIANNI , Suvash C SAHA

Eng. Manag ›› 2026, Vol. 13 ›› Issue (2) : 515 -540.

PDF (5834KB)
Eng. Manag ›› 2026, Vol. 13 ›› Issue (2) :515 -540. DOI: 10.1007/s42524-026-5136-0
Logistics Systems and Supply Chain Management
RESEARCH ARTICLE
Mitigating transportation disruptions in the Australian household hydrogen supply chain
Author information +
History +
PDF (5834KB)

Abstract

Despite growing interest in hydrogen as a clean energy source, limited research has explored the long-term operational challenges facing Australia’s household hydrogen supply chain (HHSC), particularly under transportation disruptions. This study investigates transportation disruptions in vehicles and routes within the Australian HHSC planned over the period 2026 to 2090. It focuses on disruptions across three distribution tiers: national distribution centers (NDCs), regional distribution centers (RDCs), and local distribution centers (LDCs). A multi-period network optimisation model is developed using scenario-based analysis to simulate and evaluate the impacts of various disruptive events over time. Mitigation strategies, including rerouting, additional vehicle hiring, and safety stock positioning at RDCs, are assessed for their effectiveness. The results reveal that combined disruptions, affecting both vehicles and routes, have the most severe impact on the HHSC, particularly when multiple routes and vehicles across NDCs, RDCs, and LDCs are simultaneously affected. While individual disruptions, such as those impacting only routes or only vehicles, also influence performance, their effects are comparatively less critical than the impact of combined disruptions. Mitigation strategies targeting routes, vehicles, and combined disruptions lead to higher demand fulfilment and lower penalty costs, resulting in a significant increase in overall profit. These outcomes are achieved despite the added costs associated with rerouting, additional vehicle hiring, and maintaining safety stock. The findings highlight the importance of targeted, disruption-specific planning to improve demand fulfilment and reduce penalty costs and provide practical implications for managing transportation disruptions in the HHSC.

Graphical abstract

Keywords

hydrogen supply chain / transportation disruptions / vehicle disruptions / route disruptions / disruption mitigation

Cite this article

Download citation ▾
Pranto CHAKRABARTY, Sanjoy Kumar PAUL, Andrea TRIANNI, Suvash C SAHA. Mitigating transportation disruptions in the Australian household hydrogen supply chain. Eng. Manag, 2026, 13 (2) : 515-540 DOI:10.1007/s42524-026-5136-0

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Acar CDincer I (2018). Hydrogen energy. In: I. Dincer (Ed.), Comprehensive energy systems, 1: 568–605

[2]

Acar C, Dincer I (2018a). Hydrogen energy. Comprehensive Energy Systems, 1: 568–605. Available at the website of books.google.com.au

[3]

Ahmadi-Javid A, Seddighi A H, (2023). A location-routing problem with disruption risk. Transportation Research Part E, Logistics and Transportation Review, 53: 63–82

[4]

Ahmed F, Huynh N, Ferrell W, Badyal V, Padmanabhan B, (2024). Vehicle re-routing under disruption in cross-dock network with time constraints. Expert Systems with Applications, 237: 121517

[5]

Akbari F, Valizadeh J, Hafezalkotob A, (2022). Robust cooperative planning of relief logistics operations under demand uncertainty: A case study on a possible earthquake in Tehran. International Journal of Systems Science: Operations & Logistics, 9( 3): 405–428

[6]

Aldrighetti R, Battini D, Ivanov D, Zennaro I, (2021). Costs of resilience and disruptions in supply chain network design models: A review and future research directions. International Journal of Production Economics, 235: 108103

[7]

Alizadeh T, Clements R, Legacy C, Searle G, Kamruzzaman M, (2022). Infrastructure governance in times of crises: A research agenda for Australian cities. Urban Policy and Research, 40( 1): 1–14

[8]

Allen C, Metternicht G, Wiedmann T, (2018). Initial progress in implementing the Sustainable Development Goals (SDGs): A review of evidence from countries. Sustainability Science, 13( 5): 1453–1467

[9]

Ally J, Pryor T, Pigneri A, (2015). The role of hydrogen in Australia’s transport energy mix. International Journal of Hydrogen Energy, 40( 13): 4426–4441

[10]

Almansoori A, Shah N, (2012). Design and operation of a stochastic hydrogen supply chain network under demand uncertainty. International Journal of Hydrogen Energy, 37( 5): 3965–3977

[11]

Almaraz S D L, Azzaro-Pantel C, Montastruc L, (2015). Boix M. Deployment of a hydrogen supply chain by multi-objective/multi-period optimisation at regional and national scales. Chemical Engineering Research & Design, 104: 11–31

[12]

Almaraz S D L, Rácz V, Azzaro-Pantel C, Szántó Z O, (2022). Multiobjective and social cost-benefit optimisation for a sustainable hydrogen supply chain: Application to Hungary. Applied Energy, 325: 119882

[13]

Azadnia A H, McDaid C, Andwari A M, Hosseini S E, (2023). Green hydrogen supply chain risk analysis: A european hard-to-abate sectors perspective. Renewable & Sustainable Energy Reviews, 182: 113371

[14]

Ball M, Wietschel M, Rentz O, (2007). Integration of a hydrogen economy into the German energy system: an optimising modelling approach. International Journal of Hydrogen Energy, 32( 10–11): 1355–1368

[15]

Bayram V, (2016). Optimization models for large scale network evacuation planning and management: A literature review. Surveys in Operations Research and Management Science, 21( 2): 63–84

[16]

Browning T, Kumar M, Sanders N, Sodhi M S, Thürer M, Tortorella G L, (2023). From supply chain risk to system-wide disruptions: research opportunities in forecasting, risk management and product design. International Journal of Operations & Production Management, 43( 12): 1841–1858

[17]

Chung S H, Tse Y K, Choi T M, (2015). Managing disruption risk in express logistics via proactive planning. Industrial Management & Data Systems,, 115( 8): 1481–1509

[18]

Çimen M, Benli D, İbiş Bozyel M, Soysal M, (2024). A review on sustainability, Industry 4.0 and collaboration implications in vehicle allocation operations. International Journal of Logistics Management, 35( 3): 943–978

[19]

Cox E (2021). Resilience of the future energy system: Impacts of energy disruptions on society (UKERC Working Paper). UK Energy Research Centre. Available at the website of ukerc.rl.ac.uk

[20]

Datta P P (2007). A complex system, agent-based model for studying and improving the resilience of production and distribution networks (Doctoral dissertation, Cranfield University). Cranfield University Repository. Available at the website of dspace.lib.cranfield.ac.uk

[21]

Dawood F, Shafiullah G, Anda M, (2020). A hover view over Australia’s Hydrogen Industry in recent history: the necessity for a hydrogen industry knowledge-sharing platform. International Journal of Hydrogen Energy, 45( 58): 32916–32939

[22]

Dayhim M, Jafari M A, Mazurek M, (2014). Planning sustainable hydrogen supply chain infrastructure with uncertain demand. International Journal of Hydrogen Energy, 39( 13): 6789–6801

[23]

Edwards R L, Font-Palma C, Howe J, (2021). The status of hydrogen technologies in the UK: A multi-disciplinary review. Sustainable Energy Technologies and Assessments, 43: 100901

[24]

Emenike S N, Falcone G, (2020). A review on energy supply chain resilience through optimization. Renewable & Sustainable Energy Reviews, 134: 110088

[25]

Eskandari M, Gilani H, Sahebi H, Sharifi S, (2024). Design and planning of global sustainable bio-hydrogen supply chain with uncertainty: A transportation-oriented robust model. Chemical Engineering Science, 283: 119365

[26]

Esmizadeh Y, Mellat Parast M, (2021). Logistics and supply chain network designs: incorporating competitive priorities and disruption risk management perspectives. International Journal of Logistics,, 24( 2): 174–197

[27]

Fazli-Khalaf M, Naderi B, Mohammadi M, Pishvaee M S, (2020). Design of a sustainable and reliable hydrogen supply chain network under mixed uncertainties: A case study. International Journal of Hydrogen Energy, 45( 59): 34503–34531

[28]

Fitt H, (2022). Boring and inadequate? A literature review considering the use of electric vehicles in drive tourism. Current Issues in Tourism, 25( 12): 1920–1946

[29]

Foorginezhad S, Mohseni-Dargah M, Falahati Z, Abbassi R, Razmjou A, Asadnia M, (2021). Sensing advancement towards safety assessment of hydrogen fuel cell vehicles. Journal of Power Sources, 489: 229450

[30]

Golan M S, Jernegan L H, Linkov I, (2020). Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic. Environment Systems & Decisions, 40( 2): 222–243

[31]

Gorji S A, (2023). Challenges and opportunities in green hydrogen supply chain through metaheuristic optimization. Journal of Computational Design and Engineering, 10( 3): 1143–1157

[32]

Hancock L, Wollersheim L, (2021). EU Carbon Diplomacy: Assessing Hydrogen Security and Policy Impact in Australia and Germany. Energies, 14( 23): 8103

[33]

Hassan Q, Algburi S, Sameen A Z, Jaszczur M, Salman H M, (2024). Hydrogen as an energy carrier: properties, storage methods, challenges, and future implications. Environment Systems & Decisions, 44( 2): 327–350

[34]

Humagain S, Sinha R, Lai E, Ranjitkar P, (2020). A systematic review of route optimisation and pre-emption methods for emergency vehicles. Transport Reviews, 40( 1): 35–53

[35]

Ivanov D, Dolgui A, Sokolov B, Ivanova M, (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research, 55( 20): 6158–6174

[36]

Katsaliaki K, Galetsi P, Kumar S, (2022). Supply chain disruptions and resilience: A major review and future research agenda. Annals of Operations Research, 319( 1): 965–1003

[37]

Kljaić Z, Pavković D, Cipek M, Trstenjak M, Mlinarić T J, Nikšić M, (2023). An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport. Future Internet, 15( 11): 347

[38]

Kuby M JMartinez A SKelley S B & Tal G (2023). Hydrogen station location analysis and optimization: Advanced models and behavioral evidence. Hydrogen Economy, 315–380

[39]

Moudio M P E, Bolin R, Carpenter A, Reese S B, Shehabi A & Rao P, (2022). Characterizing manufacturing sector disruptions with targeted mitigation strategies. Environmental research: infrastructure and sustainability, 2( 4): 042001

[40]

Nazib R A, Moh S, (2020). Routing protocols for unmanned aerial vehicle-aided vehicular ad hoc networks: A survey. IEEE Access : Practical Innovations, Open Solutions, 8: 77535–77560

[41]

Ng M T, Hernandez A, Durango-Cohen P L, Mahmassani H S, (2024). Trading off energy storage and payload–An analytical model for freight train configuration. Transportation Research Part E, Logistics and Transportation Review, 187: 103601

[42]

Okonkwo E C, Al-Breiki M, Bicer Y, Al-Ansari T, (2021). Sustainable hydrogen roadmap: A holistic review and decision-making methodology for production, utilisation and exportation using Qatar as a case study. International Journal of Hydrogen Energy, 46( 72): 35525–35549

[43]

Pando V, San-José L A, Sicilia J, Alcaide-López-de-Pablo D, (2024). An inventory model with price-and stock-dependent demand and time-and stock quantity-dependent holding cost under profitability maximization. Computers & Operations Research, 164: 106520

[44]

Patnala P K, Regehr J D, Mehran B, Regoui C, (2024). Resilience for freight transportation systems to disruptive events: a review of concepts and metrics. Canadian Journal of Civil Engineering, 51( 3): 237–263

[45]

Reuß M, Dimos P, Léon A, Grube T, Robinius M, Stolten D, (2021). Hydrogen road transport analysis in the energy system: A case study for Germany through 2050. Energies, 14( 11): 3166

[46]

Robles J O, Azzaro-Pantel C, Aguilar-Lasserre A, (2020). Optimization of a hydrogen supply chain network design under demand uncertainty by multi-objective genetic algorithms. Computers & Chemical Engineering, 140: 106853

[47]

Sabio N, Gadalla M, Guillén-Gosálbez G, Jiménez L, (2010). Strategic planning with risk control of hydrogen supply chains for vehicle use under uncertainty in operating costs: a case study of Spain. International Journal of Hydrogen Energy, 35( 13): 6836–6852

[48]

Sgarbossa F, Arena S, Tang O, Peron M, (2022). Renewable hydrogen supply chains: A planning matrix and an agenda for future research. International Journal of Production Economics, 250: 108712

[49]

Smit R, Helmers E, Schwingshackl M, Opetnik M, Kennedy D, (2024). Greenhouse Gas Emissions Performance of Electric, Hydrogen and Fossil-Fuelled Freight Trucks with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment (pLCA). Sustainability, 16( 2): 762

[50]

Vaidya H & Chatterji T (2020). SDG 11 Sustainable Cities and Communities: SDG 11 and the New Urban Agenda: Global Sustainability Frameworks for Local Action. Actioning the Global Goals for Local Impact: Towards Sustainability Science, Policy, Education and Practice, 173–185

[51]

Valença G, Moura F & de Sá A M, (2021). Main challenges and opportunities to dynamic road space allocation: From static to dynamic urban designs. Journal of urban mobility, 1: 100008

[52]

Visentini M S, Borenstein D, Li J Q, Mirchandani P B, (2014). Review of real-time vehicle schedule recovery methods in transportation services. Journal of Scheduling, 17( 6): 541–567

[53]

Wang G, Gunasekaran A, Ngai E W, Papadopoulos T, (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176: 98–110

[54]

Wang X, Wu Y, Wen Z, Cui Z, Wang Y, (2024). A New Transportation Route Planning Method for Wind-Based Hydrogen Supply Chains. ACS Sustainable Chemistry & Engineering, 12( 22): 8436–8452

[55]

Xu J, Bo L, (2024). Enhancing supply chain efficiency and resilience using predictive analytics and computational intelligence techniques. IEEE Access, 12: 183451–183466

[56]

Zhu Y, Jin J G, Wang H, (2024). Path-choice-constrained bus bridging design under urban rail transit disruptions. Transportation Research Part E, Logistics and Transportation Review, 188: 103637

RIGHTS & PERMISSIONS

Higher Education Press

PDF (5834KB)

660

Accesses

0

Citation

Detail

Sections
Recommended

/