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Literature review of optimization based decision model for disaster recovery planning of transportation network
Zamanifar, Milad; Hartmann, Timo
The purpose of this study is to analysis 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 review targeting DRPTN publications. Thereafter, we review the literature based on four phases of optimization-based decision-making models 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. The contributions of this paper are first, analyzing the optimization methodologies based on four phases of the optimization modeling process, second, reviewing the application of optimization in DRPTN models, and third, identifying challenges and opportunities within optimization-based DRPTN models. Eventually, we detect and discuss four research improvement areas as 1] developing conceptual or systematic support in the selection of decision factors, 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 provided suggestions as well as possible directions for future research.
