A Constraint-Based Model for Fast Post-Disaster Emergency Vehicle Routing

Abstract

Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time

A Variable Depth Search Algorithm for Binary Constraint Satisfaction Problems

“…Examples include the APACHE system [1] used at Roissy Airport in Paris, PLAN system [2] which is a medium-long term scheduling system for aircraft assembly line scheduling, the COBRA system [3] that generates work plans for train drivers and conductors of North Western Trains in the UK, and TAP-AI which is a planning system for crew assignment in the airline SAS [4]. Disasters which have long impacted world nations, resulting in mass casualties and huge financial tolls where technology and humans have to work together hand-in-hand without fault, with every single step of a mission meticulously planned out, are another research area where solutions based on constraint technology have received a great attention lately [5,6]. The handbook of Constraint Programming [7] lists example applications of several areas modeled as CSPs.…”

Managing the surge in demand for blood following mass casualty events

“…6,14,[17][18][19][20] Modeling methodologies have been applied previously in the context of MCEs, predominantly within the remit of prehospital care. [21][22][23][24][25][26][27][28] Examples of in-hospital event modeling have indicated the perceived capacity of hospitals to manage MCEs to be overly optimistic, one specifically identified blood product volume as a limiting factor in the event response. 29,30 In addition, the provision of RBCs in MCEs is time critical.…”

IJIMAI Editor�s Note - Vol. 2 Issue 4

“…Amadini et al, propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time [8].…”