A comprehensive evacuation planning model and genetic solution algorithm

Abstract

We consider the problem of evacuating an urban area caused by a natural or man-made disaster. There are several planning aspects that need to be considered in such a scenario, which are usually considered separately, due to their computational complexity. These aspects include: Which shelters are used to accommodate evacuees? How to schedule public transport for transit-dependent evacuees? And how do public and individual traffic interact? Furthermore, besides evacuation time, also the risk of the evacuation needs to be considered.We propose a macroscopic multi-criteria optimization model that includes all of these questions simultaneously. As a mixed-integer programming formulation cannot handle instances of real-world size, we develop a genetic algorithm of NSGA-II type that is able to generate feasible solutions of good quality in reasonable computation times.We extend the applicability of these methods by also considering how to aggregate instance data, and how to generate solutions for the original instance starting from a reduced solution.In computational experiments using real-world data modelling the cities of Nice in France and Kaiserslautern in Germany, we demonstrate the effectiveness of our approach and compare the trade-off between different levels of data aggregation.

Dynamic Route Network Planning Problem for Emergency Evacuation in Restricted-Space Scenarios

“…They took full advantages of the positive feedback information mechanism of ant colony algorithm and the fast convergence of the genetic algorithm [23]. For the airport emergency evacuation scenarios, the authors in [24] performed a series of simulations based on an agentbased model (ABM) to determine the collective behaviors and the overall evacuation time, which are affected by the environment and complex structures.…”

Sink location to find optimal shelters in evacuation planning

“…We assume that 25% of the population will require accomodation in specifically designated shelters and public transportation, 15% only accomodation but no public transportation, and 60% will leave the city and stay with friends or family (self-contained evacuees). The shelters for those relying on public transportation are not chosen by our model but by a different model which integrates the location of these shelters and the evacuation by buses [5]. As possible shelters we choose the 20 biggest gymnasiums in Kaiserslautern.…”

An integrated emergency response model for toxic gas release accidents based on cellular automata

“…In this stream of research, the methodologies can be roughly classified into two types: mathematical programming and simulation. Mathematical programming methods (especially integer programming) have been widely adopted to select optimal routes for evacuees Kimms 2011, 2012;Goerigk et al 2014;Lv et al 2013;Rungta et al 2012;Shen et al 2015;Saadatseresht et al 2009;Zografos and Androutsopoulos 2008). Bretschneider and Kimms (2011) propose a mixed-integer evacuation model with the objective of minimizing the evacuation time in order to provide reorganization of the traffic routing and enable fast evacuation.…”

“…Lv et al (2013) develop an emergency evacuation model using the interval-parameter joint-probabilistic integer programming (IJIP) method to obtain the optimal evacuation routes for ensuring the maximum population evacuated from the hazardous zone during a finite time. Goerigk et al (2014) propose an emergency evacuation model to provide the optimal location of shelters and the optimal evacuation routes simultaneously, considering both evacuation time and evacuation risk. It is noteworthy that, in the aforementioned papers, the evacuation routes are pre-defined and the optimal evacuation routes are selected in the pre-planning phase, with the objective of minimum evacuation distance or minimum evacuation time.…”