A Critical Survey on the Network Optimization Algorithms for Evacuation Planning Problems

In the last decades, research on emergency traffic management has received high attention from the operations research community and many pioneer researchers have established it as one of the most fertile research areas. We consider the computationally hard flows over time problems from wider perspective including flow/time dependent attributes (dynamic flows), a possibility of flows loss on paths while travelling (lossy network problems), arcs/path reversal capability (contra flow models) and possibilities of eliminating merging and crossing conflicts at intersections (abstract flows). The topics also include the networks for relief distribution, location-allocation of facilities, multi-criterion characteristics and transit based flow models in brief. The issues are highly motivated from the perspective of traffic control and emergency route choice and scheduling. Despite of many directions such as differential equations for fluid flows, measure and function theory, cell transmission approach and optimal control theory, we have restricted to the perhaps most computationally acceptable research domain, the network flow optimization approach with macroscopic behavior. We compactly review the contributions, explore the featured results, present structured systematic analysis and state the weakness and strength of the models and solution strategies the authors carried out during several years. A large number of problems belong to the category of strongly NP-hard problems and demand efficient computational techniques that at least yield acceptable approximate solutions. This comprehensive survey on evacuation problems complements the number of previous reviews by adding many recent results obtained in the field so far. Moreover, it highlights the main stream research and most promising challenges in modeling and solving more realistic real-life scenarios and explores some possible future research fi elds.


TU Bergakademie Freiberg, Fakultaet fuer Mathematik und Informatik, Preprint 2018 - 08



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