Optimization-based decision-making models for disaster recovery and reconstruction planning of transportation networks
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Optimization‑based decision‑making models for disaster recovery and reconstruction planning of transportation networks Milad Zamanifar1 · Timo Hartmann1 Received: 19 December 2019 / Accepted: 16 July 2020 © The Author(s) 2020
Abstract The purpose of this study is to analyze optimization-based decision-making models for the problem of Disaster Recovery Planning of Transportation Networks (DRPTN). In the past three decades, seminal optimization problems have been structured and solved for the critical and sensitive problem of DRPTN. The extent of our knowledge on the practicality of the methods and performance of results is however limited. To evaluate the applicability of those context-sensitive models in real-world situations, there is a need to examine the conceptual and technical structure behind the existing body of work. To this end, this paper performs a systematic search targeting DRPTN publications. Thereafter, we review the identified literature based on the four phases of the optimization-based decision-making modeling process as problem definition, problem formulation, problem-solving, and model validation. Then, through content analysis and descriptive statistics, we investigate the methodology of studies within each of these phases. Eventually, we detect and discuss four research improvement areas as [1] developing conceptual or systematic decision support in the selection of decision attributes and problem structuring, [2] integrating recovery problems with traffic management models, [3] avoiding uncertainty due to the type of solving algorithms, and [4] reducing subjectivity in the validation process of disaster recovery models. Finally, we provide suggestions as well as possible directions for future research. Keywords Disaster · Recovery · Reconstruction · Transportation network · Optimization
1 Introduction Major natural, anthropogenic, or socio-natural hazards can create unnatural disasters in vulnerable exposed societies (Chmutina and Meding 2019). On the one hand, we might not be able to contain or restrain rapid-onset natural hazards such as earthquakes any soon. Nor did we manifest much achievement to stop triggering nature on the planet to avoid socio-natural hazards namely climate change-induced floods. On the other hand, mitigating * Milad Zamanifar [email protected] 1
Department of Civil Systems, Technische Universität Berlin, Gustav‑Meyer‑Allee 25, 13355 Berlin, Germany
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the exposure of critical infrastructures, as widely broadened networks on which our civilizations are built, comes at an extreme cost and thus renders the ‘transferring risk’ a disfavored solution. Consequently, in the context of infrastructures disaster risk reduction, alternatives are limited to two main concepts of ‘reducing vulnerability’ and ‘increasing resiliency’ of infrastructures. In urban areas, the transportation network is one of the most exposed physical infrastructures (Renne et al. 2020). However, pre-planning for post-event actions substantially inc
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