Research Directions in Information Systems for Humanitarian Logistics

This article systematically reviews the literature on using IT (Information Technology) in humanitarian logistics focusing on disaster relief operations. We first discuss problems in humanitarian relief logistics. We then identify the stage and disaster type for each article as well as the article’s research methodology and research contribution. Finally, we identify potential future research directions

Optimized location-allocation of earthquake relief centers using PSO and ACO, complemented by GIS, clustering, and TOPSIS

© 2018 by the authors. After an earthquake, it is required to establish temporary relief centers in order to help the victims. Selection of proper sites for these centers has a significant effect on the processes of urban disaster management. In this paper, the location and allocation of relief centers in district 1 of Tehran are carried out using Geospatial Information System (GIS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision model, a simple clustering method and the two meta-heuristic algorithms of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). First, using TOPSIS, the proposed clustering method and GIS analysis tools, sites satisfying initial conditions with adequate distribution in the area are chosen. Then, the selection of proper centers and the allocation of parcels to them are modelled as a location/allocation problem, which is solved using the meta-heuristic optimization algorithms. Also, in this research, PSO and ACO are compared using different criteria. The implementation results show the general adequacy of TOPSIS, the clustering method, and the optimization algorithms. This is an appropriate approach to solve such complex site selection and allocation problems. In view of the assessment results, the PSO finds better answers, converges faster, and shows higher consistency than the ACO

Emergency response in complex buildings: Automated selection of safest and balanced routes

The extreme importance of emergency response in complex buildings during natural and human-induced disasters has been widely acknowledged. In particular, there is a need for efficient algorithms for finding safest evacuation routes, which would take into account the 3-D structure of buildings, their relevant semantics, and the nature and shape of hazards. In this article, we propose algorithms for safest routes and balanced routes in buildings, where an extreme event with many epicenters is occurring. In a balanced route, a trade-off between route length and hazard proximity is made. The algorithms are based on a novel approach that integrates a multiattribute decision-making technique, Dijkstra's classical algorithm and the introduced hazard proximity numbers, hazard propagation coefficient and proximity index for a route

Analysing the police patrol routing problem : a review

Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP

ОПТИМАЛЬНАЯ МАРШРУТИЗАЦИЯ ВОЗДУШНЫХ СУДОВ И МАШИН СКОРОЙ ПОМОЩИ В ЛОГИСТИКЕ ПРИ СТИХИЙНЫХ БЕДСТВИЯХ

One of the most vital aspects of emergency management studies is the development and examination of post-disaster search and rescue activities and treatment facilities. One of such issues to be considered while performing these operations is to reach the disaster victims within minimum time and to plan disaster logistics in the most efficient manner possible. In this study, the problem of planning debris scanning activities with Unmanned Aerial Vehicles after an earthquake and transporting the injured people to the hospitals by ambulances within minimum time was discussed, and mathematical models were developed to solve the problem. The ambulance routing problem and the mathematical model to be used in the solution to the problem are discussed for the first time in the literature. The developed model was tested on the problem sets created by taking into account the data of the province under investigation.Одним из наиболее важных аспектов исследований по управлению рисками и чрезвычайными ситуациями является разработка и изучение поисково-спасательных мероприятий и очистных сооружений после стихийных бедствий. Одним из вопросов, которые необходимо учитывать при выполнении этих операций, является обеспечение доступа к жертвам стихийных бедствий в минимальные сроки и планирование логистики в случае стихийных бедствий наиболее эффективным способом. В данном исследовании рассматривается проблема планирования работ по спасению с помощью беспилотных летательных аппаратов после землетрясения и транспортировки пострадавших людей в больницы на машинах скорой помощи за минимальное время. Для решения этой проблемы были разработаны и предложены математические модели. Впервые рассматривается задача маршрутизации скорой помощи и математическая модель, которая будет использоваться для решения этой задачи. Разработанная модель была протестирована на множествах задач, созданных с учетом реальных данных исследуемой провинции Турции

A smart dynamic crowd evacuation system for exhibition centers

In this paper, we consider the problem of finding the safest evacuation route in a multi-exit exhibition center while the fire hazard spreads. We first propose a system composed of sensor nodes to collect pertinent safety data. We present a real-time dynamic evacuation system that considers the changing conditions in the risks associated with each hallway segment in terms of walking distance, heat, two major asphyxiant fire gases and congestion. Our system activates smart panels placed at major junctions of the hallways to guide evacuees towards the appropriate exit by displaying the proper escape direction. This work can pave the way towards the development of next-generation smart exhibition centers, where crowd safety is among the top priorities

A Framework for Burnt Area Mapping and Evacuation Problem Using Aerial Imagery Analysis

The study aims to develop a holistic framework for maximum area coverage of a disaster region during a bushfire event. The monitoring and detection of bushfires are essential to assess the extent of damage, its direction of spread, and action to be taken for its containment. Bushfires limit human’s access to gather data to understand the ground situation. Therefore, the application of Unmanned Aerial Vehicles (UAVs) could be a suitable and technically advanced approach to grasp the dynamics of fires and take measures to mitigate them. The study proposes an optimization model for a maximal area coverage of the fire-affected region. The advanced Artificial Bee Colony (ABC) algorithm will be applied to the swarm of drones to capture images and gather data vital for enhancing disaster response. The captured images will facilitate the development of burnt area maps, locating access points to the region, estimating damages, and preventing the further spread of fire. The proposed algorithm showed optimum responses for exploration, exploitation, and estimation of the maximum height of the drones for the coverage of wildfires and it outperformed the benchmarking algorithm. The results showed that area coverage of the affected region was directly proportional to drone height. At a maximum drone height of 121 m, the area coverage was improved by 30%. These results further led to a proposed framework for bushfire relief and rescue missions. The framework is grounded on the ABC algorithm and requires the coordination of the State Emergency Services (SES) for quick and efficient disaster response

Mathematical Models in Humanitarian Supply Chain Management: A Systematic Literature Review

In the past decade the humanitarian supply chain (HSC) has attracted the attention of researchers due to the increasing frequency of disasters. The uncertainty in time, location, and severity of disaster during predisaster phase and poor conditions of available infrastructure during postdisaster phase make HSC operations difficult to handle. In order to overcome the difficulties during these phases, we need to assure that HSC operations are designed in an efficient manner to minimize human and economic losses. In the recent times, several mathematical optimization techniques and algorithms have been developed to increase the efficiency of HSC operations. These techniques and algorithms developed for the field of HSC motivate the need of a systematic literature review. Owing to the importance of mathematical modelling techniques, this paper presents the review of the mathematical contributions made in the last decade in the field of HSC. A systematic literature review methodology is used for this paper due to its transparent procedure. There are two objectives of this study: the first one is to conduct an up-to-date survey of mathematical models developed in HSC area and the second one is to highlight the potential research areas which require attention of the researchers