Olga L. Huibregtse

A method to optimize evacuation instructions

In this paper, an optimization method is presented for instructions to evacuate by car the population of a region threatened by a hazard. By giving the optimized instructions to the evacuees, traffic conditions and, therefore, the evacuation efficiency are optimized. The instructions, containing a departure time, a safe destination, and a route, are created using an optimization method consisting of two phases: the generation of the search space and the algorithm AES+ evacuation, a version of ant colony optimization. The main contributions of the proposed optimization method are the unique approach to generate the search space in which network degeneration is taken into consideration, the possibility to optimize instructions under the assumption of both full and partial compliance of the evacuees with the instructions, and the flexibility in the sense that the user of the method can define his or her own objective function and choose a suitable traffic simulation model. The paper contains a comprehensive case study. The case study shows that the effectiveness of the optimized instructions is more than doubled when compared with the effectiveness of instructions set up by straightforward rules (like evacuating to the nearest destination using the shortest route). Further, the case study shows that the number of arrivals under optimized, but possibly sub-optimal instructions is equal to at least 90% of the theoretical upper bound on this number of arrivals.

Optimizing evacuation instructions while anticipating traveler compliance behavior

Instructing evacuees on their departure time, destination and route can lead to more efficient traffic operations. Empirical findings on evacuation behavior support the view that in practice a share of travelers decides not to comply, while current evacuation plan optimization techniques are limited to assessing mandatory evacuation under the assumption of full compliance. In this contribution we show I) how traveler compliance behavior affects evacuation efficiency, and II) how evacuation efficiency can be improved in case of partial compliance when this traveler compliance is anticipated on. The optimization method and case study application presented here underline the relevance and importance of capturing traveler compliance behavior, as this has a large impact upon the evacuation efficiency.

Robust optimization of evacuation instructions, applied to capacity, hazard pattern, demand, and compliance uncertainty

In the evacuation problem, departure time, route, and destination instructions are optimized to increase the effectiveness of the evacuation (i.e., more arrivals at the destinations). In literature, evacuation instructions are mostly optimized for a problem without uncertainty (the so-called nominal problem): one specific scenario regarding the system, the hazard and the evacuees is assumed. In this paper, the robust evacuation problem is formulated to create instructions dealing with the uncertainty. So-called scenarios are used that are specific representative realizations of the various uncertainties. The effectiveness of a set of instructions is based on the worst-case performance. By solving the problem, a guarantee can be given on the number of arrivals, either absolute or relative to the number of arrivals in the solution for the nominal problem. An earlier presented optimization method is extended to solve the robust problem. In a case study, the robust evacuation problems are solved under system, hazard, demand, and behavior uncertainty. The results show that for the specific case study, the guarantee on the number of arrivals by applying the relative robustness evacuation instructions is equal to 96.1%, compared to a guarantee of 85.3% in case that only nominal problems are solved.

A Generic Method to Optimize Instructions for the Control of Evacuations

Abstract A method is described to develop a set of optimal instructions to evacuate by car the population of a region threatened by a hazard. By giving these instructions to the evacuees, traffic conditions and therefore the evacuation efficiency can be optimized. The instructions, containing a departure time, a destination, and a route, are created using an optimization method based on ant colony optimization. Iteratively is searched for an approximation of the optimal evacuation instructions. The usefulness of the optimization method compared to other optimization methods is the simultaneous optimization of the departure time, destination, and route instructions instead of the optimization of only one or two of these variables for a dynamic instead of static evacuation problem. In a case study, the functioning of the method is illustrated. The relative high fitness in the case study of the set of instructions following from the optimization method compared with the fitness of a set of instructions set up by straightforward rules (like evacuating to the nearest destination) shows also the usefulness of applying an optimization method to create a set of evacuation instructions.