Resource Allocation Based on Past Incident Patterns

TL;DR

This paper develops a resource allocation method for emergency services based on past incident data, optimizing vehicle and crew placement to minimize risk in spatial areas using a greedy algorithm.

Contribution

It introduces a minimax framework for allocating emergency resources based on incident risk, with explicit solutions and practical greedy algorithms.

Findings

Effective allocation of resources reduces risk in emergency response.

The greedy algorithm provides practical and explicit solutions.

Application to real data demonstrates the approach's utility.

Abstract

We formulate and solve two resource allocation problems motivated by a preparedness question of emergency response services. First, we consider the assignment of vehicles to stations, and, in a second step, assign crews to vehicles. In both cases, we work in a minimax framework and define the objective function for a spatial catchment area as the total risk in this area per resource unit allocated to it. The solutions are explicit and can be calculated in practice by a greedy algorithm that successively allocates a resource unit to an area having maximal relative risk, with suitable tie breaker rules. The approach is illustrated on a data set of incidents reported to the Twente Fire Brigade.