A two-stage robustness approach to evacuation planning with buses

Goerigk, Marc; Deghdak, Kaouthar; t'Kindt, Vincent

doi:10.1016/j.trb.2015.04.008

Cited by 55 publications

(18 citation statements)

References 29 publications

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“…airplane design) -it is well suited for evacuation planning. This potential has been recognised by many recent publications on robust disaster management, see, for example, Goerigk and Grün (2014), Goerigk, Deghdak, and T'Kindt (2013), Ng and Waller (2010), Chang, Tseng, and Chen (2007) and Ben-Tal et al (2011) to name just a few.…”

Section: Uncertaintymentioning

confidence: 99%

Optimisation models to enhance resilience in evacuation planning

Goerigk

Hamacher

2015

Civil Engineering and Environmental Systems

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We argue that the concepts of resilience in engineering science and robustness in mathematical optimisation are strongly related. Using evacuation planning as an example application, we demonstrate optimisation techniques to improve solution resilience. These include a direct modelling of the uncertainty for stochastic or robust optimisation as well as taking multiple objective functions into account.

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Section: Uncertaintymentioning

confidence: 99%

Optimisation models to enhance resilience in evacuation planning

Goerigk

Hamacher

2015

Civil Engineering and Environmental Systems

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“…Also, they assumed in their model that all buses are located at shelters at the beginning of process which may not be appropriate. Other studies that used robust optimization for transit‐based evacuation include Kulshrestha et al , Goerigk and Grün , and Goerigk et al .…”

Section: Literature Reviewmentioning

confidence: 99%

Strategic evacuation planning with pedestrian guidance and bus routing: a mixed integer programming model and heuristic solution

Heydar

Liu

et al. 2016

J of Advced Transportation

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Summary This paper presents a mathematical model to plan emergencies in a densely populated urban zone where a certain numbers of pedestrians depend on transit for evacuation. The proposed model features an integrated operational framework, which simultaneously guides evacuees through urban streets and crosswalks (referred to as “the pedestrian network”) to designated pickup points (e.g., bus stops), and routes a fleet of buses at different depots to those pick‐up points and transports evacuees to their destinations or safe places. In this level, the buses are routed through the so‐called “vehicular network.” An integrated mixed integer linear program that can effectively take into account the interactions between the aforementioned two networks is formulated to find the maximal evacuation efficiency in two networks. Because the large instances of the proposed model are mathematically difficult to solve to optimality, a two‐stage heuristic is developed to solve larger instances of the model. Results from hundreds of numerical examples analysis indicate that proposed heuristic works well in providing (near) optimal or feasibly good solutions for medium‐scale to large‐scale instances that may arise in real transit‐based evacuation situations in a much shorter amount of computational time compared with cplex (can find optimal/feasible solutions for only five instances within 3 hours of running). Copyright © 2016 John Wiley & Sons, Ltd.

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“…For a variant of this problem, [GGH13] propose several Branch-and-Bound algorithms. Robust bus evacuation models have been considered in [GG14,GDT13].…”

Section: Related Literaturementioning

confidence: 99%

A comprehensive evacuation planning model and genetic solution algorithm

Goerigk

Deghdak

Heßler

2014

Transportation Research Part E: Logistics and Transportation Re

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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.

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A two-stage robustness approach to evacuation planning with buses

Cited by 55 publications

References 29 publications

Optimisation models to enhance resilience in evacuation planning

Optimisation models to enhance resilience in evacuation planning

Strategic evacuation planning with pedestrian guidance and bus routing: a mixed integer programming model and heuristic solution

A comprehensive evacuation planning model and genetic solution algorithm

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