Browsing by Author "Bayram, V."
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Item Open Access Humanitarian logistics under uncertainty: planning for sheltering and evacuation(Springer Cham, 2023-05-09) Bayram, V.; Y. Kara, Bahar; Saldanha-da-Gama, F.; Yaman, H.; Eiselt, H. A.; Marianov, V.This chapter focuses on a major area emerging in the context of humanitarian logistics: emergency evacuation planning and management. Two major aspects are covered: shelter site location and evacuation traffic assignment. Both are discussed separately before an integrated problem is considered. Throughout the chapter, uncertainty in the underlying parameters is assumed. The major sources of uncertainty analyzed are the demand for sheltering and capacity of the edges in the underlying network. Congestion issues emerge in this context that are also considered. Different paradigms for capturing uncertainty are considered for illustrative purposes, namely, robust optimization, chance-constrained programming, and stochastic programming.Item Open Access Shelter location and evacuation route assignment under uncertainty: a benders decomposition approach(INFORMS Inst.for Operations Res.and the Management Sciences, 2018) Bayram, V.; Yaman, HandeShelters 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 Open Access A stochastic programming approach for Shelter location and evacuation planning(EDP Sciences, 2018) Bayram, V.; Yaman, HandeShelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values