Oruç Ağlar, Buse Eylül2018-08-012018-08-012018-062018-062018-07-12http://hdl.handle.net/11693/47707Cataloged from PDF version of article.Thesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2018.Includes bibliographical references (leaves 78-86).Post-disaster assessment operations constitute the basis for the operations conducted in the response phase of the disaster management. Through the assessment of the road segments, the extent of damage and the amount of debris will be determined, and debris removal operations will benefit from this assessment. Via assessing the damage at the population centers, the needs of the affected area will be determined and the distribution of relief supplies will be made accordingly. Hence, the damage assessment allows disaster management operation coordinators to determine immediate actions necessary to respond to the effects of the disaster with the effective use of resources for alleviating human suffering. In this study, we propose a post-disaster assessment strategy as part of response operations in which effective and fast relief routing are of utmost importance. In particular, the road segments and the population points to perform assessment activities on are selected based on the value they add to the consecutive response operations. To this end, we develop a bi-objective mathematical model that utilizes a heterogeneous vehicle set. The proposed model for disaster assessment considers motorcycles, which can be utilized under off-road conditions, and/or unmanned-aerial-vehicles, drones. The first objective aims to maximize the total value added by the assessment of the road segments (arcs) whereas the second maximizes the total profit generated by assessing points of interests (nodes). Bi-objectivity of the problem is studied with the -constraint method. Since obtaining solutions as fast as possible is crucial in the post-disaster condition, heuristic methods are also proposed. To test the mathematical model and the heuristic methods, a data set belonging to Kartal district of Istanbul is usedxii, 90 leaves : illustrations ; 30 cm.Englishinfo:eu-repo/semantics/openAccessDisaster ManagementHumanitarian LogisticsBi-ObjectiveGeneral RoutingThesisB158623