IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i4p979-996.html
   My bibliography  Save this article

Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response

Author

Listed:
  • Wapee Manopiniwes
  • Takashi Irohara

Abstract

This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.

Suggested Citation

  • Wapee Manopiniwes & Takashi Irohara, 2017. "Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 979-996, February.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:979-996
    DOI: 10.1080/00207543.2016.1211340
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1211340
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2016.1211340?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Angappa Gunasekaran & Nachiappan Subramanian & Shams Rahman, 2015. "Supply chain resilience: role of complexities and strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6809-6819, November.
    3. Sheu, Jiuh-Biing, 2007. "Challenges of emergency logistics management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 655-659, November.
    4. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    5. Galindo, Gina & Batta, Rajan, 2013. "Review of recent developments in OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 230(2), pages 201-211.
    6. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    7. Beraldi, P. & Bruni, M.E., 2009. "A probabilistic model applied to emergency service vehicle location," European Journal of Operational Research, Elsevier, vol. 196(1), pages 323-331, July.
    8. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    9. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
    10. Kelle, Peter & Schneider, Helmut & Yi, Huizhi, 2014. "Decision alternatives between expected cost minimization and worst case scenario in emergency supply – Second revision," International Journal of Production Economics, Elsevier, vol. 157(C), pages 250-260.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Afshin Kamyabniya & Antoine Sauré & F. Sibel Salman & Noureddine Bénichou & Jonathan Patrick, 2024. "Optimization models for disaster response operations: a literature review," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(3), pages 737-783, September.
    2. Faraz Salehi & Masoud Mahootchi & Seyed Mohammad Moattar Husseini, 2019. "Developing a robust stochastic model for designing a blood supply chain network in a crisis: a possible earthquake in Tehran," Annals of Operations Research, Springer, vol. 283(1), pages 679-703, December.
    3. Abazari, Seyed Reza & Aghsami, Amir & Rabbani, Masoud, 2021. "Prepositioning and distributing relief items in humanitarian logistics with uncertain parameters," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    4. Jamal Al Qundus & Kosai Dabbour & Shivam Gupta & Régis Meissonier & Adrian Paschke, 2022. "Wireless sensor network for AI-based flood disaster detection," Annals of Operations Research, Springer, vol. 319(1), pages 697-719, December.
    5. Sara Cheraghi & Seyyed-Mahdi Hosseini-Motlagh, 2020. "Responsive and reliable injured-oriented blood supply chain for disaster relief: a real case study," Annals of Operations Research, Springer, vol. 291(1), pages 129-167, August.
    6. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    7. Zeinab Sazvar & Mahsa Zokaee & Reza Tavakkoli-Moghaddam & Samira Al-sadat Salari & Sina Nayeri, 2022. "Designing a sustainable closed-loop pharmaceutical supply chain in a competitive market considering demand uncertainty, manufacturer’s brand and waste management," Annals of Operations Research, Springer, vol. 315(2), pages 2057-2088, August.
    8. Fang Xu & Yifan Ma & Chang Liu & Ying Ji, 2024. "Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments," Sustainability, MDPI, vol. 16(4), pages 1-34, February.
    9. Jin, Zhongyi & Ng, Kam K.H. & Zhang, Chenliang & Liu, Wei & Zhang, Fangni & Xu, Gangyan, 2024. "A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    10. Xuehong Gao, 2019. "A Novel Reverse Logistics Network Design Considering Multi-Level Investments for Facility Reconstruction with Environmental Considerations," Sustainability, MDPI, vol. 11(9), pages 1-22, May.
    11. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    12. Hongbin Liu & Guopeng Song & Tianyu Liu & Bo Guo, 2022. "Multitask Emergency Logistics Planning under Multimodal Transportation," Mathematics, MDPI, vol. 10(19), pages 1-25, October.
    13. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    14. Khanchehzarrin, Saeed & Ghaebi Panah, Mona & Mahdavi-Amiri, Nezam & Shiripour, Saber, 2022. "A bi-level multi-objective location-routing optimization model for disaster relief operations considering public donations," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    15. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    16. Raquel Sanchis & Alfonso Duran-Heras & Raul Poler, 2020. "Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming," Mathematics, MDPI, vol. 8(9), pages 1-29, September.
    17. Aghajani, Mojtaba & Torabi, S. Ali & Heydari, Jafar, 2020. "A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    18. Rabin K. Jana & Dinesh K. Sharma & Peeyush Mehta, 2022. "A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials," Annals of Operations Research, Springer, vol. 319(1), pages 149-172, December.
    19. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    20. Sohrabi, Mahnaz & Zandieh, Mostafa & Shokouhifar, Mohammad, 2023. "Sustainable inventory management in blood banks considering health equity using a combined metaheuristic-based robust fuzzy stochastic programming," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    21. Wapee Manopiniwes & Takashi Irohara, 2021. "Optimization model for temporary depot problem in flood disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 1743-1763, January.
    22. Seyed Reza Abazari & Fariborz Jolai & Amir Aghsami, 2022. "Designing a humanitarian relief network considering governmental and non-governmental operations under uncertainty," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1430-1452, June.
    23. Baharmand, Hossein & Comes, Tina & Lauras, Matthieu, 2019. "Bi-objective multi-layer location–allocation model for the immediate aftermath of sudden-onset disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 86-110.
    24. Ali Torabi, S. & Shokr, Iman & Tofighi, Saeideh & Heydari, Jafar, 2018. "Integrated relief pre-positioning and procurement planning in humanitarian supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 123-146.
    25. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yanyan Wang & Baiqing Sun, 2022. "Multiperiod optimal emergency material allocation considering road network damage and risk under uncertain conditions," Operational Research, Springer, vol. 22(3), pages 2173-2208, July.
    2. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    3. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    4. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    5. Nihal Berktaş & Bahar Yetiş Kara & Oya Ekin Karaşan, 2016. "Solution methodologies for debris removal in disaster response," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 403-445, September.
    6. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    7. Yiping Jiang & Yufei Yuan, 2019. "Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges," IJERPH, MDPI, vol. 16(5), pages 1-23, March.
    8. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    9. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    10. Qi, Mingyao & Yang, Ying & Cheng, Chun, 2023. "Location and inventory pre-positioning problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    11. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    12. Pouraliakbari-Mamaghani, Mahsa & Saif, Ahmed & Kamal, Noreen, 2023. "Reliable design of a congested disaster relief network: A two-stage stochastic-robust optimization approach," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    13. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    14. Özdamar, Linet & Ertem, Mustafa Alp, 2015. "Models, solutions and enabling technologies in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 244(1), pages 55-65.
    15. Rodríguez-Espíndola, Oscar & Albores, Pavel & Brewster, Christopher, 2018. "Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods," European Journal of Operational Research, Elsevier, vol. 264(3), pages 978-993.
    16. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    17. Li, Xiaoping & Batta, Rajan & Kwon, Changhyun, 2017. "Effective and equitable supply of gasoline to impacted areas in the aftermath of a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 25-34.
    18. Ying Lu & Shuqi Sun, 2020. "Scenario-Based Allocation of Emergency Resources in Metro Emergencies: A Model Development and a Case Study of Nanjing Metro," Sustainability, MDPI, vol. 12(16), pages 1-21, August.
    19. Rezaei-Malek, Mohammad & Tavakkoli-Moghaddam, Reza & Cheikhrouhou, Naoufel & Taheri-Moghaddam, Alireza, 2016. "An approximation approach to a trade-off among efficiency, efficacy, and balance for relief pre-positioning in disaster management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 485-509.
    20. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2016. "Online optimization of casualty processing in major incident response: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 252(1), pages 334-348.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:979-996. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.