A Fuzzy Decision Support Model for Natural Disaster Response under Informational Uncertainty

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 address this issue of operational emergency response in natural disaster management (NDM) by suggesting a decision support model and a Monte Carlo heuristic which account for these challenges by drawing on fuzzy set theory and fuzzy optimization.Deriving requirements for addressing NDM situations from both practice and literature, we propose a decision model that accounts for the following phenomena: a) incidents and rescue units are spatially distributed, b) rescue units possess specific capabilities, c) processing is non-preemptive, and d) informational uncertainty occurs due to vague and linguistic specifications of data. We computationally evaluate our heuristic and benchmark the results with current best practice solutions. Our results indicate that applying the new heuristic can substantially reduce overall harm.

Human Resource Management in Emergency Situations

“…Wex et al (2012) computationally evaluate our heuristic and benchmark the results with current best practice solutions. Wex et al (2012) results indicate that applying the new heuristic can substantially reduce overall harm.…”

“…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 (Wex et al 2012). Wex et al (2012) address this issue of operational emergency response in natural disaster management (NDM) by suggesting a decision support model and a Monte Carlo heuristic which account for these challenges by drawing on fuzzy set theory and fuzzy optimization.…”

“…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 (Wex et al 2012). Wex et al (2012) address this issue of operational emergency response in natural disaster management (NDM) by suggesting a decision support model and a Monte Carlo heuristic which account for these challenges by drawing on fuzzy set theory and fuzzy optimization. Deriving requirements for addressing NDM situations from both practice and literature, Wex et al (2012) propose a decision model that accounts for the following phenomena: a) incidents and rescue units are spatially distributed, b) rescue units possess specific capabilities, c) processing is non-preemptive, and d) informational uncertainty occurs due to vague and linguistic specifications of data.…”

“…Wex et al (2012) address this issue of operational emergency response in natural disaster management (NDM) by suggesting a decision support model and a Monte Carlo heuristic which account for these challenges by drawing on fuzzy set theory and fuzzy optimization. Deriving requirements for addressing NDM situations from both practice and literature, Wex et al (2012) propose a decision model that accounts for the following phenomena: a) incidents and rescue units are spatially distributed, b) rescue units possess specific capabilities, c) processing is non-preemptive, and d) informational uncertainty occurs due to vague and linguistic specifications of data. Wex et al (2012) computationally evaluate our heuristic and benchmark the results with current best practice solutions.…”

Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization

“…The purpose of this model is to minimize the number of supply points and the start time of emergency rescue. In view of the complexity of emergency resources, some researchers have built corresponding multi-objective models [20,[23][24][25]. Stevenson K A [26][27][28] et al proposed a three-dimensional mesh model related to ambulance scheduling, which is designed to solve the problem of rapid and reasonable scheduling of a large number of ambulances.…”