|
|
Michael R. Bartolacci, Christoph Aubrecht, & Dilek Ozceylan Aubrecht. (2014). A portable base station optimization model for wireless infrastructure deployment in disaster planning and management. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 50–54). University Park, PA: The Pennsylvania State University.
Abstract: Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts.
|
|
|
|
Mauro Falasca, Christopher W. Zobel, & Gary M. Fetter. (2009). An optimization model for humanitarian relief volunteer management. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: One of the challenges of humanitarian organizations is that there exist limited decision technologies that fit their needs. It has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. The purpose of this paper is to help address those challenges through the development of a decision model to assist in the management of volunteers. While employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this paper, we discuss a series of principles from the field of volunteer management and develop a multi criteria optimization model to assist in the assignment of volunteers to tasks. We present an illustrative example and analyze a solution methodology where the decision maker exercises his/her preferences by trading-off conflicting objectives. Conclusions, limitations, and directions for future research are also discussed.
|
|
|
|
P. Lin, & S.M. Lo. (2005). The application of quickest flow problem in urban evacuation planning. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 129–130). Brussels: Royal Flemish Academy of Belgium.
Abstract: The provision of evacuation plan for people living in populated urban area is necessary to reduce the possible casualties under disasters. Time-varying quickest flow problem (TVQFP), which can simultaneously optimize the evacuation schedule, evacuation locations and evacuation routes, is adopted to optimize the evacuation planning of a city to minimize the clearance time of residents in danger. The integration of optimization model with GIS environment enables emergency managers to easily identify possible bottlenecks and to observe evacuation patterns in vivid pictures for further analysis and evaluation.
|
|
|
|
Michael R. Bartolacci, Albena Mihovska, & Dilek Ozceylan Aubrecht. (2013). Optimization modeling and decision support for wireless infrastructure deployment in disaster planning and management. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 674–677). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Natural disasters and emergencies create the need for communication between and among the affected populace and emergency responders as well as other parties such as governmental agencies and aid organizations. Such communications include the dissemination of key information such as evacuation orders and locations of emergency shelters. In particular, the coordination of efforts between responding organizations require additional communication solutions that typically rely heavily on wireless communications to complement fixed line infrastructure due to the ease of use and portability. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall cost to deploy. This work does not focus on the question of what entity will operate the portable base stations or wireless equipment utilized during a disaster, only the question of optimizing placement for planning and real time management purposes. This work examines current wireless network optimization models and points out that none of them include the necessary variables for a disaster planning or emergency deployment context. Due to the fact that the choice of wireless technology impacts the nature of an overall model, a brief discussion of exemplar wireless technologies is included. The work also proposes criteria that must be taken into account in order to have a useful model for deployment of mobile base stations and related wireless communications equipment.
|
|
