Abstract

In the humanitarian context, two-stage stochastic programming is of special interest as it allows for modeling uncertainties and time-dependent decisions. Since natural disasters are highly unpredictable, the magnitude of the damage that will result cannot be determined in advance and hence, modeling uncertainties is a major challenge in the humanitarian decision making process. Two-stage programming is an issue, as some decisions have to be made before uncertainty is realized, and some can be made only afterwards. This paper reviews the state-of-the-art literature of the last decade on this topic with a special emphasis on modeling and solution approaches. In particular, the survey compares and classifies the respective models according to the disaster phase in which they are applied and to their objectives, underlying assumptions and special features. A variety of solution techniques are presented in the relevant literature; also these are discussed and critically evaluated in this work. Moreover, future research directions with respect to modeling and solution approaches, especially for large-scale problems, are recommended.

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