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Shelter location and evacuation route assignment under uncertainty: a Benders decomposition approach

Bayram, Vedat, Yaman, Hande (2018) Shelter location and evacuation route assignment under uncertainty: a Benders decomposition approach. Transportation Science, 52 (2). pp. 416-436. ISSN 0041-1655. E-ISSN 1526-5447. (doi:10.1287/trsc.2017.0762) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:99643)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
https://dx.doi.org/10.1287/trsc.2017.0762

Abstract

Shelters are safe facilities that protect a population from possible damaging effects of a disaster. For that reason, shelter location and traffic assignment decisions should be considered simultaneously for an efficient evacuation plan. In addition, as it is very difficult to anticipate the exact place, time, and scale of a disaster, one needs to take into account the uncertainty in evacuation demand, the disruption/degradation of evacuation road network structure, and the disruption in shelters. In this study, we propose an exact algorithm based on Benders decomposition to solve a scenario-based two-stage stochastic evacuation planning model that optimally locates shelters and that assigns evacuees to shelters and routes in an efficient and fair way to minimize the expected total evacuation time. The second stage of the model is a second-order cone programming problem, and we use duality results for second-order cone programming in a Benders decomposition setting. We solve practical-size problems with up to 1,000 scenarios in moderate CPU times. We investigate methods such as employing a multicut strategy, deriving Pareto-optimal cuts, and using a preemptive priority multiobjective program to enhance the proposed algorithm. We also use a cutting plane algorithm to solve the dual subproblem since it contains a constraint for each possible path. Computational results confirm the efficiency of our algorithms.

Item Type: Article
DOI/Identification number: 10.1287/trsc.2017.0762
Uncontrolled keywords: disaster management; evacuation traffic management; shelter location; constrained system optimal; two-stage stochastic programming; Benders decomposition; second-order cone programming; cutting plane algorithm
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: TED University (https://ror.org/0285rh439)
Depositing User: Vedat Bayram
Date Deposited: 23 Jan 2023 09:50 UTC
Last Modified: 01 Feb 2023 11:54 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/99643 (The current URI for this page, for reference purposes)

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