Flow Improvement in Evacuation Planning with Budget Constrained Switching Costs

Many large-scale natural and human-created disasters have drawn the attention of researchers towards the solutions of evacuation planning problems and their applications. The main focus of these solution strategies is to protect the life, property, and their surroundings during the disasters. With limited resources, it is not an easy task to develop a universally accepted model to handle such issues. Among them, the budget-constrained network flow improvement approach plays significant role to evacuate the maximum number of people within the given time horizon. In this paper, we consider an evacuation planning problem that aims to shift a maximum number of evacuees from a danger area to a safe zone in limited time under the budget constraints for network modification. Different flow improvement strategies with respect to fixed switching cost will be investigated, namely, integral, rational, and either to increase the full capacity of an arc or not at all. A solution technique on static network is extended to the dynamic one. Moreover, we introduce the static and dynamic maximum flow problems with lane reversal strategy and also propose efficient algorithms for their solutions. Here, the contraflow approach reverses the direction of arcs with respect to the lane reversal costs to increase the flow value. As an implementation of an evacuation plan may demand a large cost, the solutions proposed here with budget constrained problems play important role in practice.

[1]  Éva Tardos,et al.  Efficient continuous-time dynamic network flow algorithms , 1998, Oper. Res. Lett..

[2]  Tanka Nath Dhamala,et al.  Abstract Contraflow Models and Solution Procedures for Evacuation Planning , 2018, Journal of Mathematics Research.

[3]  Panos M. Pardalos,et al.  Complexity analysis for maximum flow problems with arc reversals , 2010, J. Comb. Optim..

[4]  Tanka Nath Dhamala,et al.  Partial contraflow with path reversals for evacuation planning , 2018, Ann. Oper. Res..

[5]  Shashi Shekhar,et al.  Contraflow network reconfiguration for evacuation planning: a summary of results , 2005, GIS '05.

[6]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[7]  Stephan Dempe,et al.  Efficient Dynamic Flow Algorithms for Evacuation Planning Problems with Partial Lane Reversal , 2019, Mathematics.

[8]  Sven O. Krumke,et al.  Flow Improvement and Network Flows with Fixed Costs , 1999 .

[9]  Dmitrii Lozovanu,et al.  The maximum flow in dynamic networks , 2004, Comput. Sci. J. Moldova.

[10]  Tanka Nath Dhamala,et al.  Efficient contraflow algorithms for quickest evacuation planning , 2018, Science China Mathematics.

[11]  Bin Ran,et al.  An Integrated Contraflow Strategy for Multimodal Evacuation , 2014 .

[12]  Tanka Nath Dhamala,et al.  Continuous Time Dynamic Contraflow Models and Algorithms , 2016, Adv. Oper. Res..

[13]  Nimrod Megiddo,et al.  Combinatorial optimization with rational objective functions , 1978, Math. Oper. Res..

[14]  Stephan Dempe,et al.  A Critical Survey on the Network Optimization Algorithms for Evacuation Planning Problems , 2018 .

[15]  Sven Oliver Krumke,et al.  On Budget-Constrained Flow Improvement , 1998, Inf. Process. Lett..

[16]  Panos M. Pardalos,et al.  Minimum concave-cost network flow problems: Applications, complexity, and algorithms , 1991 .

[17]  Eric V. Denardo,et al.  Flows in Networks , 2011 .

[18]  Shashi Shekhar,et al.  Contraflow Transportation Network Reconfiguration for Evacuation Route Planning , 2008, IEEE Transactions on Knowledge and Data Engineering.

[19]  Mingxia Gao,et al.  An Improved Critical-Edge Model for Finding Optimal Contraflow Links Considering the Influence of Intersections , 2019, Mathematical Problems in Engineering.

[20]  H. W. Hamacher,et al.  Mathematical Modelling of Evacuation Problems: A State of Art , 2001 .

[21]  Tanka Nath Dhamala,et al.  Evacuation planning by earliest arrival contraflow , 2016 .