A disaster relief operations management model: a hybrid LP–GA approach

People are always threatened by natural disasters which usually cause significant losses. Therefore, planning for confronting such situations is a vast dilemma. In this paper, a general model is proposed to address the uncertain demand of disaster-stricken areas. Demand from injured people relates to the vulnerability of regions that depends on the quality of buildings and severity of damage. In the studied problem, the commodities collected from relief centers, donations and storage warehouses are distributed to the shelters. It aims at minimizing the total cost, and unfulfilled demand and maximizing the coverage and accessibility of relief centers. The LP-metric approach is utilized to solve the multi-objective model, and a scenario-based optimization is used to incorporate the uncertainty in the proposed model. Moreover, an LP–GA method is proposed for optimizing large-scale instances. Several problems in different scales are solved to show its flexibility and time-efficiency. Finally, a case study of an earthquake disaster in Amol city in Iran is presented. The obtained results suggest better service in the distressed urban areas.

[1]  Mohamad Saeed Jabalameli,et al.  A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty , 2011, OR Spectrum.

[2]  Peter A. Rogerson,et al.  A logistics model for emergency supply of critical items in the aftermath of a disaster , 2011 .

[3]  Mitsuo Gen,et al.  Genetic algorithms and engineering design , 1997 .

[4]  D. Guha-Sapir,et al.  EM-DAT: The CRED/OFDA International Disaster Database , 2016 .

[5]  Sasan Barak,et al.  A genetic algorithm based grey goal programming (G3) approach for parts supplier evaluation and selection , 2012 .

[6]  Seyed Jafar Sadjadi,et al.  A robust optimization model for humanitarian relief chain design under uncertainty , 2016 .

[7]  Walter J. Gutjahr,et al.  Bi-objective bilevel optimization of distribution center locations considering user equilibria , 2016 .

[8]  Charles S. ReVelle,et al.  The Location of Emergency Service Facilities , 1971, Oper. Res..

[9]  Mohammad Saadi Mesgari,et al.  Evaluation and comparison of Genetic Algorithm and Bees Algorithm for location–allocation of earthquake relief centers , 2016 .

[10]  Shafii Muhammad Abdulhamid,et al.  Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm , 2016, Neural Computing and Applications.

[11]  Mitsuo Gen,et al.  A steady-state genetic algorithm for multi-product supply chain network design , 2009, Comput. Ind. Eng..

[12]  Mahdi Heydari,et al.  A modified particle swarm optimization for disaster relief logistics under uncertain environment , 2012 .

[13]  Han-Lin Li,et al.  A robust optimization model for stochastic logistic problems , 2000 .

[14]  Luís Santos,et al.  A Multiobjective Approach to Locate Emergency Shelters and Identify Evacuation Routes in Urban Areas , 2009 .

[15]  Linet Özdamar,et al.  Emergency Logistics Planning in Natural Disasters , 2004, Ann. Oper. Res..

[16]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[17]  Iraj Mahdavi,et al.  A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem , 2016 .

[18]  M. Horner,et al.  The effects of transportation network failure on people’s accessibility to hurricane disaster relief goods: a modeling approach and application to a Florida case study , 2011 .

[19]  Robert J. Vanderbei,et al.  Robust Optimization of Large-Scale Systems , 1995, Oper. Res..

[20]  Iraj Mahdavi,et al.  A hybrid GA-AUGMECON method to solve a cubic cell formation problem considering different worker skills , 2014, Comput. Ind. Eng..

[21]  Reza Tavakkoli-Moghaddam,et al.  Robust humanitarian relief logistics network planning , 2014 .

[22]  Shao-Long Hu,et al.  A scenario planning approach for propositioning rescue centers for urban waterlog disasters , 2015, Comput. Ind. Eng..

[23]  Kathrin Fischer,et al.  Inventory relocation for overlapping disaster settings in humanitarian operations , 2011, OR Spectr..

[24]  Yujun Zheng,et al.  Emergency transportation planning in disaster relief supply chain management: a cooperative fuzzy optimization approach , 2013, Soft Comput..