| Records |
Author  |
Felix Wex; Guido Schryen; Dirk Neumann |
| Title |
Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units |
Type |
Conference Article |
| Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Decision support systems; Fuzzy set theory; Information systems; Monte Carlo methods; Optimization; Computational evaluation; Coordination; Decision support models; Fuzzy optimization model; Heuristic solutions; Informational uncertainty; Linguistic assessment; Operational emergency; Scheduling |
| Abstract |
Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM. |
| Address |
Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany |
| Corporate Author |
|
Thesis |
|
| Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780864913326 |
Medium |
|
| Track |
Intelligent Systems |
Expedition |
|
Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
238 |
| Share this record to Facebook |
| |
|
| |
| Author |
Felix Wex; Guido Schryen; Dirk Neumann |
| Title |
Intelligent decision support for centralized coordination during Emergency Response |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Information systems; Intelligent systems; Optimization; Resource allocation; Allocation mechanism; Comparative analysis; Coordination; Distributed resource allocation; Emergency operations centers; Emergency response systems; Intelligent decision support; Monte-Carlo simulations; Decision support systems |
| Abstract |
Automated coordination is regarded as a novel approaches in Emergency Response Systems (ERS), and especially resource allocation has been understudied in former research. The contribution of this paper is the introduction of two variants of a novel resource allocation mechanism that provide decision support to the centralized Emergency Operations Center (EOC). Two quantitative models are computationally validated using real-time, data-driven, Monte-Carlo simulations promoting reliable propositions of distributed resource allocations and schedules. Various requirements are derived through a literature analysis. Comparative analyses attest that the Monte-Carlo approach outperforms a well-defined benchmark. |
| Address |
Albert-Ludwigs-Universität Freiburg, Germany; Universität Regensburg, Germany |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
|
| Track |
Intelligent Systems |
Expedition |
|
Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
1077 |
| Share this record to Facebook |
| |
|
| |
| Author |
Gerhard Rauchecker; Guido Schryen |
| Title |
Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief |
Type |
Conference Article |
| Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
| Volume |
|
Issue |
|
Pages |
69-82 |
| Keywords |
Coordination of spontaneous volunteers, volunteer coordination system, decision support, scheduling optimization model, linear programming |
| Abstract |
When responding to natural disasters, professional relief units are often supported by many volunteers which are not affiliated to humanitarian organizations. The effective coordination of these volunteers is crucial to leverage their capabilities and to avoid conflicts with professional relief units. In this paper, we empirically identify key requirements that professional relief units pose on this coordination. Based on these requirements, we suggest a decision model. We computationally solve a real-world instance of the model and empirically validate the computed solution in interviews with practitioners. Our results show that the suggested model allows for solving volunteer coordination tasks of realistic size near-optimally within short time, with the determined solution being well accepted by practitioners. We also describe in this article how the suggested decision support model is integrated in the volunteer coordination system, which we develop in joint cooperation with a disaster management authority and a software development company. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
|
| Track |
Analytical Modeling and Simulation |
Expedition |
|
Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
2091 |
| Share this record to Facebook |
