Modeling and optimization for spatial detection to minimize abandonment rate

dc.contributor.advisorMorton, David P.
dc.contributor.advisorHasenbein, John J.
dc.creatorLu, Fang, active 21st centuryen
dc.date.accessioned2014-09-18T18:45:50Zen
dc.date.accessioned2018-01-22T22:26:31Z
dc.date.available2018-01-22T22:26:31Z
dc.date.issued2014-08en
dc.date.submittedAugust 2014en
dc.date.updated2014-09-18T18:45:50Zen
dc.descriptiontexten
dc.description.abstractSome oil and gas companies are drilling and developing fields in the Arctic Ocean, which has an environment with sea ice called ice floes. These companies must protect their platforms from ice floe collisions. One proposal is to use a system that consists of autonomous underwater vehicles (AUVs) and docking stations. The AUVs measure the under-water topography of the ice floes, while the docking stations launch the AUVs and recharge their batteries. Given resource constraints, we optimize quantities and locations for the docking stations and the AUVs, as well as the AUV scheduling policies, in order to provide the maximum protection level for the platform. We first use an queueing approach to model the problem as a queueing system with abandonments, with the objective to minimize the abandonment probability. Both M/M/k+M and M/G/k+G queueing approximations are applied and we also develop a detailed simulation model based on the queueing approximation. In a complementary approach, we model the system using a multi-stage stochastic facility location problem in order to optimize the docking station locations, the AUV allocations, and the scheduling policies of the AUVs. A two-stage stochastic facility location problem and several efficient online scheduling heuristics are developed to provide lower bounds and upper bounds for the multi-stage model, and also to solve large-scale instances of the optimization model. Even though the model is motivated by an oil industry project, most of the modeling and optimization methods apply more broadly to any radial detection problems with queueing dynamics.en
dc.description.departmentOperations Research and Industrial Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/25998en
dc.language.isoenen
dc.subjectSpatial detectionen
dc.subjectQueues with abandonmentsen
dc.subjectSimulationen
dc.subjectStochastic programmingen
dc.subjectMulti-stage stochastic facility location problemen
dc.subjectScheduling heuristicsen
dc.titleModeling and optimization for spatial detection to minimize abandonment rateen
dc.typeThesisen

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