Since the 1950s, the number of natural and man-made disasters has increased exponentially and the facility location problem has become the preferred approach for dealing with emergency humanitarian logistical problems. To deal with this challenge, an exact algorithm and a heuristic algorithm have been combined as the main approach to solving this problem. Owing to the importance that an exact algorithm holds with regard to enhancing emergency humanitarian logistical facility location problems, this paper aims to conduct a survey on the facility location problems that are related to emergency humanitarian logistics based on both data modeling types and problem types and to examine the pre- and post-disaster situations with respect to facility location, such as the location of distribution centers, warehouses, shelters, debris removal sites and medical centers. The survey will examine the four main problems highlighted in the literature review: deterministic facility location problems, dynamic facility location problems, stochastic facility location problems, and robust facility location problems. For each problem, facility location type, data modeling type, disaster type, decisions, objectives, constraints, and solution methods will be evaluated and real-world applications and case studies will then be presented. Finally, research gaps will be identified and be addressed in further research studies to develop more effective disaster relief operations.

Facility location optimization model for emergency humanitarian logistics

Multicriteria optimization in humanitarian aid

The field of supply chain management has been extensively studied, while its role in disaster relief operations has received limited contributions. Recent dedicated special issues on Humanitarian Operations and Supply Chain Management (HOSCM) and a dedicated Journal focusing on humanitarian logistics and supply chain management clearly indicate the growing popularity of the HOSCM literature. The purpose of our current study is to undertake an extensive review of extant literature published in operations and supply chain management journals as well as popular interdisciplinary journals. A review of 362 papers published between 2011 and 2017 provides a thematic outline of the study. The study pivots around nine key themes, which have gained prominent attention from HOSCM scholars, and draws a roadmap from reviewing earlier review papers to performance evaluation of HOSCM related studies. Some of the key themes include humanitarian logistics, theory focused research, case studies, mathematical models, humanitarian supply chain properties and resources needed for efficient and effective management of humanitarian operations. Finally, our study offers several research directions which may take the existing debates to a next level.

Humanitarian supply chain management: a thematic literature review and future directions of research

Disaster preparedness in humanitarian logistics:A collaborative approach for resource management in floods

An interactive approach for designing a robust disaster relief logistics network with perishable commodities

Thousands of victims and millions of affected people are consequences of natural disasters, every year. Therefore, it is essential to prepare a proper response program that considers early activities of disaster management. In urban areas, local organizations and municipal authorities are responsible for disaster-related operations such as providing emergency shelters, proper equipment, and relief supplies in order to reduce sufferings of survivors. In this paper, a new multi-objective mixed-integer linear programming model is developed for preparation planning phase of disaster management. The proposed model is inspired from a real case study of an urban district in Iran, which considers both humanitarian- and cost-based objectives in a goal-programming approach. Proactive damage estimation result of Risk Assessment tool for Diagnosis of Urban Areas against Seismic Disaster software is used as an input in order to allocate affected people to local emergency management facilities that should be established. The location allocation model is solved for both current municipal subregional zoning and a virtual zoning approach that creates auxiliary cells. Mathematical results show that the second approach can reduce logistic costs and increase total coverage simultaneously. In other words, using virtual zones would help the authorities create a better collaboration between neighboring local areas and as a result, efficiency of the decisions improves.

A multi-objective relief chain location distribution model for urban disaster management

Article history: Received June 2 2013 Received in revised format August 15 2013 Accepted August 15 2013 Available online August 31 2013 In recent decays, there has been an extensive improvement in technology and knowledge; hence, human societies have started to fortify their urban environment against the natural disasters in order to diminish the context of vulnerability. Local administrators as well as government officials are thinking about new options for disaster management programs within their territories. Planning to set up local disaster management facilities and stock pre-positioning of relief items can keep an urban area prepared for a natural disaster. In this paper, based on a realworld case study for a municipal district in Tehran, a multi-objective mathematical model is developed for the location-distribution problem. The proposed model considers the role of demand in an urban area, which might be affected by neighbor wards. Integrating decisionmaking process for a disaster helps to improve a better relief operation during response phase of disaster management cycle. In the proposed approach, a proactive damage estimation method is used to estimate demands for the district based on worst-case scenario of earthquake in Tehran. Since such model is designed for an entire urban district, it is considered to be a large-scale mixed integer problem and hence, a genetic algorithm is developed to solve the model. © 2013 Growing Science Ltd. All rights reserved

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V. Esmaeili

Papers

A multi-objective relief chain location distribution model for urban disaster management

Integrated decision making model for urban disaster management: A multi-objective genetic algorithm approach