Abstract




 
   

IJE TRANSACTIONS C: Aspects Vol. 31, No. 6 (June 2018) 932-942   

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  RE-CONFIGURATION OF THE RELIEF NETWORK CONSIDERING UNCERTAIN DEMAND AND LINK FAILURE IN AN EARTHQUAKE: A MULTI-STAGE STOCHASTIC PROGRAMMING
 
H. R. Rezaei, H. Khademi Zare, M. Bashiri and M. B. Fakhrzad
 
( Received: April 17, 2017 – Accepted in Revised Form: February 27, 2018 )
 
 

Abstract    Disasters inevitably trigger far-reaching consequences affecting all living things and the environment. Therefore, top managers and decision-makers in disaster management seek comprehensive approaches to evaluate facilities and network preparedness in dealing with the response phase of predicted disaster scenarios in terms of number of casualties, costs, and unmet demands. In this regard, previous studies on the preparedness phase have often been limited to the location of eligible facilities without considering other important factors such as current assets, entities and configuration. Thus, the present study proposes a reconfiguring and repositioning model in order to simultaneously assess whether existing support bases should remain, be consolidated or phased out as well as whether new support base facilities should be established and subsequently supply and demand requirements considered. In the proposed model, in addition to considering a scenario tree for destruction and demands, network links affected by the intensity of disaster events are also evaluated. Furthermore, in order to increase reliability, the destruction of network links takes into account that link failures give rise to vulnerability in related links. In the proposed model, multi-stage stochastic programming has been implemented on various real destruction and demand scenarios. The results indicate definite advantages in the re-positioning or reconfiguring model compared with current configurations. Moreover, the superior capability of the applied solving approach versus one of the traditional approaches is also appraised.

 

Keywords    Disaster Management, Re-configuring, Re-positioning, Preparedness Facility, Multi-stage Stochastic Programming, Scenario Tree, Link Damage.

 

چکیده    بحران ها همواره و بی تردید اثرات و پیامدهای انسانی و غیر انسانی جدی را ایجاد می نمایند به نحوی که مدیران و تصمیم سازان کلان این حوزه به دنبال رویکردهایی برای ارزیابی سطح آمادگی کنونی پیکره بندی تسهیلات خود از نظر میزان تلفات، هزینه ها و تقاضاهای برآورده نشده در مواجهه با بحران پیش بینی شده در برنامه ریزی فازهای آمادگی و پاسخ می باشند. در این راستا، تحقیقات کنونی در فاز آمادگی اغلب محدود به مکان یابی تسهیلات جدید بدون توجه و ملاحظه ی دارایی ها، موجودیت ها و پیکره بندی های موجود می باشد. در این مقاله، یک مدل موقعیت یابی یا پیکره بندی مجدد پیشنهاد شده است تا به طور همزمان در خصوص نگهداری یا بستن تسهیلات کنونی نگهداری و توزیع اقلام امداد در مراکز پشتیبانی، احداث تسهیلات جدید، نحوه ی ادغام تسهیلات بلا استفاده با سایر تسهیلات فعال و همچنین نحوه جریان امداد میان سطوح تامین کنندگان، مراکز پشتیبان (مراکز توزیع) و نقاط تقاضا تصمیم سازی گردد. در مدل پیشنهادی، علاوه بر ملاحظه ی یک درخت سناریو برای ویرانی های زلزله و تقاضاها، لینک های شبکه نیز تحت تاثیر شدت رخدادهای بحران در درخت سناریو قرار می گیرند. بنابراین، تخریب لینک ها به نحوی در نظر گرفته شده اند که لینک های خراب و ویران منجر به بسته شده نزدیک ترین لینک ها با مقاومت کمتر خواهند شد. به منظور حل مدل، یک رویکرد برنامه ریزی چند مرحله ای تصادفی بر دو مسئله با سناریوهای تخریب و تقاضاهای واقعی اعمال گردیده است. نتایج، برتری محسوس را در پیکره بندی مجدد پیشنهادی در قیاس با پیکره بندی موجودنشان می دهد. همچنین بهبود بکارگیری روش برنامه ریزی تصادفی چند مرحله ای در مقابل یکی از روش های سنتی نیز مورد بررسی قرار گرفته است.

References   

1.     Peeta, S., Salman, F.S., Gunnec, D. and Viswanath, K., "Pre-disaster investment decisions for strengthening a highway network", Computers & Operations Research,  Vol. 37, No. 10, (2010), 1708-1719.

2.     Beraldi, P. and Bruni, M.E., "A probabilistic model applied to emergency service vehicle location", European Journal of Operational Research,  Vol. 196, No. 1, (2009), 323-331.

3.     Hoyos, M.C., Morales, R.S. and Akhavan-Tabatabaei, R., "Or models with stochastic components in disaster operations management: A literature survey", Computers & Industrial Engineering,  Vol. 82, (2015), 183-197.

4.     Rawls, C.G. and Turnquist, M.A., "Pre-positioning and dynamic delivery planning for short-term response following a natural disaster", Socio-Economic Planning Sciences,  Vol. 46, No. 1, (2012), 46-54.

5.     Rawls, C.G. and Turnquist, M.A., "Pre-positioning of emergency supplies for disaster response", Transportation research part B: Methodological,  Vol. 44, No. 4, (2010), 521-534.

6.     Florez, J.V., Lauras, M., Okongwu, U. and Dupont, L., "A decision support system for robust humanitarian facility location", Engineering Applications of Artificial Intelligence,  Vol. 46, (2015), 326-335.

7.     Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Cheikhrouhou, N. and Taheri-Moghaddam, A., "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,  Vol. 93, (2016), 485-509.

8.     Gutjahr, W.J. and Nolz, P.C., "Multicriteria optimization in humanitarian aid", European Journal of Operational Research,  Vol. 252, No. 2, (2016), 351-366.

9.     Rodríguez-Espíndola, O. and Gaytán, J., "Scenario-based preparedness plan for floods", Natural Hazards,  Vol. 76, No. 2, (2015), 1241-1262.

10.   Ahmadi, M., Seifi, A. and Tootooni, B., "A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on san francisco district", Transportation Research Part E: Logistics and Transportation Review,  Vol. 75, (2015), 145-163.

11.   Noyan, N., "Risk-averse two-stage stochastic programming with an application to disaster management", Computers & Operations Research,  Vol. 39, No. 3, (2012), 541-559.

12.   Rawls, C.G. and Turnquist, M.A., "Pre-positioning planning for emergency response with service quality constraints", OR Spectrum,  Vol. 33, No. 3, (2011), 481-498.

13.   Hong, X., Lejeune, M.A. and Noyan, N., "Stochastic network design for disaster preparedness", IIE Transactions,  Vol. 47, No. 4, (2015), 329-357.

14.   Shishebori, D., "Study of facility location-network design problem in presence of facility disruptions: A case study (research note)", International Journal of Engineering-Transactions A: Basics,  Vol. 28, No. 1, (2014), 97.

15.   Bozorgi-Amiri, A. and Asvadi, S., "A prioritization model for locating relief logistic centers using analytic hierarchy process with interval comparison matrix", Knowledge-Based Systems,  Vol. 86, (2015), 173-181.

16.   Zarrinpoor, N., Fallahnezhad, M. and Pishvaeeb, M., "Design of a reliable facility location model for health service networks", International Journal of Engineering-Transactions A: Basics,  Vol. 30, No. 1, (2017), 75-84.

17.   Mulvey, J.M., Vanderbei, R.J. and Zenios, S.A., "Robust optimization of large-scale systems", Operations Research,  Vol. 43, No. 2, (1995), 264-281.

18.   Jia, H., Ordóńez, F. and Dessouky, M.M., "Solution approaches for facility location of medical supplies for large-scale emergencies", Computers & Industrial Engineering,  Vol. 52, No. 2, (2007), 257-276.

19.   Verma, A. and Gaukler, G.M., "Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches", Computers & Operations Research,  Vol. 62, (2015), 197-209.

20.   Salman, F.S. and Yucel, E., "Emergency facility location under random network damage: Insights from the istanbul case", Computers & Operations Research,  Vol. 62, (2015), 266-281.

21.   Zolfaghari, M. and Peyghaleh, E., "Probabilistic earthquake scenarios for the city of tehran", in Proceedings of the 14th European Conference of Earthquake Engineering. (2010).

22.          Escudero, L.F., Garin, A., Merino, M. and Pérez, G., "The value of the stochastic solution in multistage problems", Top,  Vol. 15, No. 1, (2007), 48-64.


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