Model and a solution algorithm for the dynamic resource allocation problem for large-scale transportation network evacuation |
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| Institution: | 1. NEXTRANS Center, Purdue University, 3000 Kent Avenue, West Lafayette, IN 47906, USA;2. School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA;1. Shanghai Maritime University, No. 1550, Harbour Rd., New district, Pudong, Shanghai 201306, China;2. Tokyo Institute of Technology, M1-11, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552, Japan;1. School of Astronautics, Harbin Institute of Technology, Harbin 150080, China;2. Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia;3. Nonlinear Analysis and Applied Mathematics Research Group (NAAM) and Mathematics Department, Faculty of Science and Arts (Khulais), King Abdulaziz University, Jeddah 21589, Saudi Arabia;1. Lille 1 University, LAGIS, UMR CNRS 8164, Lille, France;2. Lebanese University, Doctoral School for Sciences and Technology, AZM Center for Research in Biotechnology, Tripoli, Lebanon;3. Université de Technologie de Belfort-Montbéliard, Laboratoire Systèmes et Transports, Belfort, France |
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| Abstract: | Allocating movable resources dynamically enables evacuation management agencies to improve evacuation system performance in both the spatial and temporal dimensions. This study proposes a mixed integer linear program (MILP) model to address the dynamic resource allocation problem for transportation evacuation planning on large-scale networks. The proposed model is built on the earliest arrival flow formulation that significantly reduces problem size. A set of binary variables, specifically, the beginning and the ending time of resource allocation at a location, enable a strong formulation with tight constraints. A solution algorithm is developed to solve for an optimal solution on large-scale network applications by adopting Benders decomposition. In this algorithm, the MILP model is decomposed into two sub-problems. The first sub-problem, called the restricted master problem, identifies a feasible dynamic resource allocation plan. The second sub-problem, called the auxiliary problem, models dynamic traffic assignment in the evacuation network given a resource allocation plan. A numerical study is performed on the Dallas–Fort Worth network. The results show that the Benders decomposition algorithm can solve an optimal solution efficiently on a large-scale network. |
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| Keywords: | Evacuation planning Resource allocation Mixed integer linear program Benders decomposition |
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