Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 12 Sayı: 2, 520 - 528, 30.06.2020
https://doi.org/10.29137/umagd.727311

Öz

Kaynakça

  • Bastian, N.D., Griffin, P.M., Spero, E., and Fulton, L.V. (2016) Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations, Optimization Letters, 10, 921-953.
  • Besiou, M. and Van Wassenhove, L.N. (2019) Humanitarian Operations: A World of Opportunity for Relevant and Impactful Research, Manufacturign & Service Operations Management, 1-11.
  • Brauers, W.K.M (2002) The Multiplicative Representation for Multiple Objectives Optimization with an Application for Arms Procurement, Naval Research Logistics, 49.
  • Brauers, W.K.M. (2004) Optimization methods for a stakeholder society. A revolution in economic thinking by multiobjective optimization: Nonconvex Optimization and its Applications, Kluwer Academic Publishers, Boston, U.S.A.
  • Brauers, W.K.M. and Zavadskas, E.K. (2006) The MOORA method and its application to privatization in a transition economy, Control and Cybernetic, 35(2), 445-469.
  • Brauers, W.K.M., and Zavadskas, E.K. (2010) Project management by MULTIMOORA as an instrument for transition economies, Technological and Economic Development of Economy, 16(1), 524.
  • Brauers, W.K.M., and Zavadskas, E.K. (2012) Robustness of MULTIMOORA: A Method for Multi-Objective Optimization, Informatica, 23(1), 1-25.
  • Brauers, W.K.M., Balezentis, A. & Balezentis, T. (2011). Multimoora for the EU member states updated with fuzzy number theory. Technological and Economic Development of Economy, 17(2), 259-290.
  • Celik, E., Taskin Gumus, A., and Alegoz, M. (2014) A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management, Journal of Intelligent & Fuzzy Systems, 27, 2847-2855.
  • Chen, C.T., Lin, C.T. and Huang, S.F. (2006) A fuzzy approach for supplier evaluation and selection in supply chain management, International Journal of Production Economics, 102(2), 289-301.
  • Drakaki, M., Güner Gören, H., and Tzionas, P. (2018) An intelligent multi-agent based decision support system for refugee settlement siting, International Journal of Disaster Risk Reduction, 31, 576-588.
  • Elluru, S., Gupta, H., Kaur, H., and Singh, S.P. (2019) Proactive and Reactive Models for Disaster Resilient Supply Chain, Annals of Operations Research, 283, 199-224.
  • Falagala Sigala, I., and Wakolbinger T. (2019) Outsourcing of Humanitarian Logistics to Commercial Logistics Service Providers, Journal of Humanitarian Logistics and Supply Chain Management, 9(1), 47-69.
  • Gadakh, V.S. (2011) Application of MOORA Method for Parametric Optimization of Milling Process, International Journal of Applied Engineerıng Research, Dindigul. 1(4).
  • Goldschmidt, K.H. and Kumar, S. (2019) Reducing the cost of humanitarian operations through disaster preparation and preparedness, Annals of Operatiosl Research, 283, 1139-1152.
  • Gossler, T., Wakolbinger, T., Nagurney, A., & Daniele, P. (2019) How to Increase The Impact of Disaster Relief: A Study of Transpotation Rates, Framework Agreements and Product Distribution. European Journal of Operational Research, 274, 126-141.
  • Heaslip, G., Vaillancourt, A., Tatham, P., Kovacs, G., Blackman, D. and Crowley Henry, M. (2019) Supply Chain and Logistics Competencies in Humanitarian Aid, Disasters, 43(3), 686-708.
  • Kako, M., Steenkamp, M., Ryan, B., Arbon, P., and Takada, Y. (2020) Best practice for evacuation centres accommodating vulnerable populations: A literature review, International Journal of Disaster Risk Reduction, 46, 101497.
  • Kim, S., Ramkumar, M., and Subramanian, N. (2019) Logistics service provider selection for disaster preparation: A Socio-technical systems perspective, Annals of Operations Research, 283, 1259-1282.
  • Kimber, L.R. (2019) Resilience from the United Nations Standpoint: The Challenges of “Vagueness”, In: SpringerBriefs in Applied Sciences and Technology, 89-96, SpringerVerlag.
  • Redmond, A.D. (2005) ABC of Conflict and Disaster: Needs Assessment of Humanitarian Crises, British Medical Journal, 330 (7503), 1320-1322.
  • Resodihardjo, S.L. (2018) Introduction to the Special Issue: Humanitarian Organizations in Disaster Response. Risk, Hazards & Crisis in Public Policy, 9(2), 104-106.
  • Rodriguez-Espindola, O., Albores, P., and Brewster, C. (2018) Decision-making and Operations in Disasters: Challenges and Opportunities, International Journal of Operations & Production Management, 38(10): 1964-1986.
  • Roh, S., Jang, H., and Han, C. (2013) Warehouse location decision factors in humanitarian relief logistics, The Asian Journal of Shipping and Logistics, 29(1), 103-120.
  • Roh, S., Pettit, S., Harris, I., and Beresford, A. (2015) The pre-positioning of warehouses at regional and local levels for a humanitarian relief organization, International Journal of Production Economics, 170B, 616-628.
  • Rose, J. and O’Keefe, P. (2017) Relief Operations, In: International Encyclopedia of Public Health, 2nd Edition, Academic Pres, 278-285.
  • Saksrisathaporn, K., Bouras, A., Reeveerakul, N., and Charles, A. (2016) Application of decision model by using an integration of AHP and TOPSIS approaches within humanitarian operation life cycle, International Journal of Information Technology & Decision Making, 15(4), 887-918.
  • Saksrisathaporn, K., and Reeveerakul, N. (2016) An implementation of a decision model: A national and international relief operation comparison, 6th International Conference of Information Systems, Logistics and Supply Chain, June 1-4, Bordeaux, France.
  • Smirnov, A., Kashevnik, A., Levashova, T., and Shilov, N. (2007) Context-Driven Information Fusion for Operational Decision Making in Humanitarian Logistics, In: Information Fusion and Geographic Information Systems, Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg.
  • Song, S., Zhou, H., and Song, W. (2019) Sustainable shelter-site selection under uncertainty: A rough QUALIFLEX method, Computers & Industrial Engineering, 128, 371-386.
  • Stauffer, J.M., Pedraza-Martinez, A.J., Yan, L., Van Wassenhove, L.N. (2018) Asset Supply Networks in Humanitarian Operations: A Combined Empirical-Simulation Approach, Journals of Operational Management, 63, 44-58.
  • Stephenson Jr, M. (2005) Making Humanitarian Relief Networks More Effective: Operational Coordination, Trust and Sense Making, Disasters, 29(4), 337-350.
  • Tomasini, R. and Van Wassenhove, L.N. (2009) Humanitarian Logistics, Palgrave Macmillan, Basingstoke, UK.
  • UN Humanitarian Response Depot (2018) World Food Programme: http://www1.wfp.org/unhrd
  • Van Wassenhove, L.N. (2006) Humanitarian aid logistics: Supply Chain Management in High Gear. Journal of Operational Research Society, 57(5), 475-489.
  • Venkatesh, V.G., Zhang, A., Deakins, E., Luthra, S., and Mangla, S. (2019) A fuzzy AHP-TOPSIS approach to supply partner selection in continuous aid humanitarian supply chains, Annals of Operations Research, 283,1517-1550.
  • World Food Programme (2020) Zero hunger: http://www.wfp.org/zero-hunger.

Multi Criteria Decision Making for the Selection of a New Hub Facility Location in Humanitarian Supply Chains

Yıl 2020, Cilt: 12 Sayı: 2, 520 - 528, 30.06.2020
https://doi.org/10.29137/umagd.727311

Öz

Trying to help people affected by hundreds of disasters around the world, is a necessity of being a “human” and an important movement for all humanity. As part of these efforts, humanitarian agencies and academicians have been focusing on humanitarian logistics. The World Food Programme (WFP) is one of the leading organizations that help over 80 million people every year. According to WFP, almost half of the necessary materials are supplied in the country or region where the crisis is located, and the other half is supplied and shipped internationally. These international grants are provided by the United Nations Humanitarian Depots managed by the WFP. The key elements of this network are the centers located close to the disaster areas where the emergency materials are stored. In this study, a decision support plan has been proposed to choose among suitable new facility candidates evaluated for use when necessary. In the multi-criteria decision-making problem discussed, alternative locations are examined according to the related criteria such as immediate mobilization, cost efficiency, stability of the hosting zone, disaster-prone area, training abilities for humanitarian services, and economies of scale. A robust method is used considering the linguistic evaluations, together with the fuzzy information.

Kaynakça

  • Bastian, N.D., Griffin, P.M., Spero, E., and Fulton, L.V. (2016) Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations, Optimization Letters, 10, 921-953.
  • Besiou, M. and Van Wassenhove, L.N. (2019) Humanitarian Operations: A World of Opportunity for Relevant and Impactful Research, Manufacturign & Service Operations Management, 1-11.
  • Brauers, W.K.M (2002) The Multiplicative Representation for Multiple Objectives Optimization with an Application for Arms Procurement, Naval Research Logistics, 49.
  • Brauers, W.K.M. (2004) Optimization methods for a stakeholder society. A revolution in economic thinking by multiobjective optimization: Nonconvex Optimization and its Applications, Kluwer Academic Publishers, Boston, U.S.A.
  • Brauers, W.K.M. and Zavadskas, E.K. (2006) The MOORA method and its application to privatization in a transition economy, Control and Cybernetic, 35(2), 445-469.
  • Brauers, W.K.M., and Zavadskas, E.K. (2010) Project management by MULTIMOORA as an instrument for transition economies, Technological and Economic Development of Economy, 16(1), 524.
  • Brauers, W.K.M., and Zavadskas, E.K. (2012) Robustness of MULTIMOORA: A Method for Multi-Objective Optimization, Informatica, 23(1), 1-25.
  • Brauers, W.K.M., Balezentis, A. & Balezentis, T. (2011). Multimoora for the EU member states updated with fuzzy number theory. Technological and Economic Development of Economy, 17(2), 259-290.
  • Celik, E., Taskin Gumus, A., and Alegoz, M. (2014) A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management, Journal of Intelligent & Fuzzy Systems, 27, 2847-2855.
  • Chen, C.T., Lin, C.T. and Huang, S.F. (2006) A fuzzy approach for supplier evaluation and selection in supply chain management, International Journal of Production Economics, 102(2), 289-301.
  • Drakaki, M., Güner Gören, H., and Tzionas, P. (2018) An intelligent multi-agent based decision support system for refugee settlement siting, International Journal of Disaster Risk Reduction, 31, 576-588.
  • Elluru, S., Gupta, H., Kaur, H., and Singh, S.P. (2019) Proactive and Reactive Models for Disaster Resilient Supply Chain, Annals of Operations Research, 283, 199-224.
  • Falagala Sigala, I., and Wakolbinger T. (2019) Outsourcing of Humanitarian Logistics to Commercial Logistics Service Providers, Journal of Humanitarian Logistics and Supply Chain Management, 9(1), 47-69.
  • Gadakh, V.S. (2011) Application of MOORA Method for Parametric Optimization of Milling Process, International Journal of Applied Engineerıng Research, Dindigul. 1(4).
  • Goldschmidt, K.H. and Kumar, S. (2019) Reducing the cost of humanitarian operations through disaster preparation and preparedness, Annals of Operatiosl Research, 283, 1139-1152.
  • Gossler, T., Wakolbinger, T., Nagurney, A., & Daniele, P. (2019) How to Increase The Impact of Disaster Relief: A Study of Transpotation Rates, Framework Agreements and Product Distribution. European Journal of Operational Research, 274, 126-141.
  • Heaslip, G., Vaillancourt, A., Tatham, P., Kovacs, G., Blackman, D. and Crowley Henry, M. (2019) Supply Chain and Logistics Competencies in Humanitarian Aid, Disasters, 43(3), 686-708.
  • Kako, M., Steenkamp, M., Ryan, B., Arbon, P., and Takada, Y. (2020) Best practice for evacuation centres accommodating vulnerable populations: A literature review, International Journal of Disaster Risk Reduction, 46, 101497.
  • Kim, S., Ramkumar, M., and Subramanian, N. (2019) Logistics service provider selection for disaster preparation: A Socio-technical systems perspective, Annals of Operations Research, 283, 1259-1282.
  • Kimber, L.R. (2019) Resilience from the United Nations Standpoint: The Challenges of “Vagueness”, In: SpringerBriefs in Applied Sciences and Technology, 89-96, SpringerVerlag.
  • Redmond, A.D. (2005) ABC of Conflict and Disaster: Needs Assessment of Humanitarian Crises, British Medical Journal, 330 (7503), 1320-1322.
  • Resodihardjo, S.L. (2018) Introduction to the Special Issue: Humanitarian Organizations in Disaster Response. Risk, Hazards & Crisis in Public Policy, 9(2), 104-106.
  • Rodriguez-Espindola, O., Albores, P., and Brewster, C. (2018) Decision-making and Operations in Disasters: Challenges and Opportunities, International Journal of Operations & Production Management, 38(10): 1964-1986.
  • Roh, S., Jang, H., and Han, C. (2013) Warehouse location decision factors in humanitarian relief logistics, The Asian Journal of Shipping and Logistics, 29(1), 103-120.
  • Roh, S., Pettit, S., Harris, I., and Beresford, A. (2015) The pre-positioning of warehouses at regional and local levels for a humanitarian relief organization, International Journal of Production Economics, 170B, 616-628.
  • Rose, J. and O’Keefe, P. (2017) Relief Operations, In: International Encyclopedia of Public Health, 2nd Edition, Academic Pres, 278-285.
  • Saksrisathaporn, K., Bouras, A., Reeveerakul, N., and Charles, A. (2016) Application of decision model by using an integration of AHP and TOPSIS approaches within humanitarian operation life cycle, International Journal of Information Technology & Decision Making, 15(4), 887-918.
  • Saksrisathaporn, K., and Reeveerakul, N. (2016) An implementation of a decision model: A national and international relief operation comparison, 6th International Conference of Information Systems, Logistics and Supply Chain, June 1-4, Bordeaux, France.
  • Smirnov, A., Kashevnik, A., Levashova, T., and Shilov, N. (2007) Context-Driven Information Fusion for Operational Decision Making in Humanitarian Logistics, In: Information Fusion and Geographic Information Systems, Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg.
  • Song, S., Zhou, H., and Song, W. (2019) Sustainable shelter-site selection under uncertainty: A rough QUALIFLEX method, Computers & Industrial Engineering, 128, 371-386.
  • Stauffer, J.M., Pedraza-Martinez, A.J., Yan, L., Van Wassenhove, L.N. (2018) Asset Supply Networks in Humanitarian Operations: A Combined Empirical-Simulation Approach, Journals of Operational Management, 63, 44-58.
  • Stephenson Jr, M. (2005) Making Humanitarian Relief Networks More Effective: Operational Coordination, Trust and Sense Making, Disasters, 29(4), 337-350.
  • Tomasini, R. and Van Wassenhove, L.N. (2009) Humanitarian Logistics, Palgrave Macmillan, Basingstoke, UK.
  • UN Humanitarian Response Depot (2018) World Food Programme: http://www1.wfp.org/unhrd
  • Van Wassenhove, L.N. (2006) Humanitarian aid logistics: Supply Chain Management in High Gear. Journal of Operational Research Society, 57(5), 475-489.
  • Venkatesh, V.G., Zhang, A., Deakins, E., Luthra, S., and Mangla, S. (2019) A fuzzy AHP-TOPSIS approach to supply partner selection in continuous aid humanitarian supply chains, Annals of Operations Research, 283,1517-1550.
  • World Food Programme (2020) Zero hunger: http://www.wfp.org/zero-hunger.
Toplam 37 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Makaleler
Yazarlar

Gül Didem Batur Sir 0000-0002-5226-2964

Emre Çalışkan 0000-0002-6262-7197

Yayımlanma Tarihi 30 Haziran 2020
Gönderilme Tarihi 26 Nisan 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 12 Sayı: 2

Kaynak Göster

APA Batur Sir, G. D., & Çalışkan, E. (2020). Multi Criteria Decision Making for the Selection of a New Hub Facility Location in Humanitarian Supply Chains. International Journal of Engineering Research and Development, 12(2), 520-528. https://doi.org/10.29137/umagd.727311
Tüm hakları saklıdır. Kırıkkale Üniversitesi, Mühendislik Fakültesi.