Scheduling algorithm based on follow-up sharing character for post-event response resource distribution in large-scal disasters

Abstract

Post-event response planners must develop effective and efficient plans for the proper allocation and distribution of resources to impacted areas (IAs) within a critical time window. To determine the effectiveness and efficiency of distribution plans, this study addresses resource allocation effectiveness losses (RAEL, or losses caused by the mismatch between supply and demand in IAs) and emergency logistics time costs (ELTC, or transportation time of logistics processes under emergency conditions). Moreover, this study examines a follow-up sharing character (FSC) that coordinates resources among different phases. This research proposes an integrated model (IM) based on this character. This model aims to minimize RAEL and ELTC. Furthermore, the IM combines the time dimension model (TDM), which coordinates the demands and supplies of all phases in the planning horizon, and the space dimension model (SDM), which generates a specific distribution plan for the first phase. An analytical solution is obtained for the TDM as per the definition of FSC, after which the SDM is solved through a single-objective linear programming model. After solving the IM effectively, we find that the proposed methodology fits the emergency circumstance well. Insights derived from the model are also presented in the conclusion.)

Keywords

Emergency management / humanitarian logistics / decision-making / resource distribution

References

[1] Arora H., Raghu T.S., Vinze A.. Resource allocation for demand surge mitigation during disaster response.. Decision Support Systems, 2010, 50: 304-315.

[2] Balcik B., Beamon B.M., Smilowitz K.. Last mile distribution in humanitarian relief.. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 2008, 12: 51-63.

[3] Barbarosoglu G., Arda Y.. A two-stage stochastic programming framework for transportation planning in disaster response.. Journal of the Operational Research Society, 2004, 55: 43-53.

[4] Barbarosoglu G., Özdamar L., Çevik A.. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations.. European Journal of Operational Research, 2002, 140: 118-133.

[5] Ben-Tal A., Chung B.D., Mandala S.R., Yao T.. Robust optimization for emergency logistics planning: risk mitigation in humanitarian relief supply chains.. Transportation Research Part B Methodological, 2011, 45: 1177-1189.

[6] Brandeau M.L., Zaric G.S., Richter A.. Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis.. Journal of Health Economics, 2003, 22: 575-598.

[7] Chiu Y.C., Zheng H.. Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups: model formulation and solution.. Transportation Research, Part E, 2007, 43: 710-736.

[8] Fiedrich F., Gehbauer F., Rickers U.. Optimized resource allocation for emergency response after earthquake disasters.. Safety Science, 2000, 35: 41-57.

[9] Haghani A., Oh S.C.. Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations.. Transportation Research, Part A, 1996, 30: 231-250.

[10] Haghani A., Yan S.Y., Shih Y.L.. Optimal scheduling of emergency roadway repair and subsequent relief distribution, 2009.

[11] Hu, Z.H.(2011). A container multimodal transportation scheduling approach based on immune affinity model for emergency relief. Expert Systems with Applications, 38: 2632–2639.

[12] Jotshi A., Gong Q., Ba R.J.. Dispatching and routing of emergency vehicles in disaster mitigation using data fusion.. Socio-Economic Planning Sciences, 2009, 43: 1-24.

[13] Liu N., Ye Y.. Humanitarian logistics planning for natural disaster response with Bayesian information updates.. Journal of Industrial and Management Optimization, 2014, 10(3): 665-689.

[14] Malilay J., Flanders W.D., Brogan D.. A modified cluster-sampling method for post-disaster rapid assessment of needs.. Bulletin of the World Health Organization, 1996, 74: 399-405.

[15] Miller-Hooks E.D., Mahmassani H.S.. Least possible time paths in stochastic, time-varying networks.. Computers Ops Res, 1998, 25: 1107-1125.

[16] Özdamar L., Ekinci E., KÜÇÜkyazic B.. Emergency logistics planning in natural disasters.. Annals of Operations Research, 2004, 129: 217-245.

[17] Özdamar A., Yi W.. Greedy Neighborhood search for disaster relief and evacuation logistics.. IEEE Intelligent Systems, 2008, 23: 14-23.

[18] Rawls C.G., Turnquis M.A.. Pre-positioning of emergency supplies for disaster response.. Transportation Research, Part B, 2010, 44: 521-534.

[19] Sheu, J.B.(2007). An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research, Part E, 43: 687–709.

[20] Sheu, J.B.(2010). Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transportation Research, Part E, 46: 1–17.

[21] Sheu J.B., Chen Y.H., Lan L.W.. A novel model for quick response to disaster relief distribution.. Proceedings of the Eastern Asia Society for Transportation Studies, 2005, 5: 2454-2462.

[22] Tufekci S., Wallace W.A.. The emerging area of emergency management and engineering.. IEEE Transactions on Engineering Management, 1998, 45: 103-105.

[23] Tzeng G.H., Cheng H.J., Huang T.D.. Multi-objective optimal planning for designing relief delivery systems.. Transportation Research, Part E, 2007, 43: 673-686.

[24] UNCRD(2009). Reconnaissance Report of the 2008 Sichuan Earthquake. Japanese Edition. Match.

[25] Widener M.J., Horner M.W.. A hierarchical approach to modeling hurricane disaster relief goods distribution.. Journal of Transport Geography, 2011, 19: 821-828.

[26] Yi W., Kumar A.. Ant colony optimization for disaster relief operations.. Transportation Research, Part E, 2007, 43: 660-672.

[27] Yi W., Özdamar L.. A dynamic logistics coordination model for evacuation and support in disaster response activities European.. Journal of Operational Research, 2007, 179: 1177-1193.

[28] Yuan Y., Wang D.W.. Path selection model and algorithm for emergency logistics management.. Computers & Industrial Engineering, 2009, 56: 1081-1094.