Spelling suggestions: "subject:"amathematical aptimization"" "subject:"amathematical foptimization""
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Augmented Lagrangian and differentiable exact penalty methodsJanuary 1981 (has links)
Dimitri P. Bertsekas. / "July 1981" / Bibliography: leaves 13-14. / "National Science Foundation Grant no. NSF/ECS 79-20834."
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Flow control and routing techniques for integrated voice and data networksJanuary 1981 (has links)
Oliver C. Ibe. / Bibliography: p.25-26. / "October 1981" / "ARPA Grant No. N00014-75-C-1183"
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Supply chain planning using network flow optimizationWang, Shentao. January 2003 (has links) (PDF)
Thesis (master's)--Dalhousie University (Canada), 2003. / Adviser: Uday Venkatadri. Includes bibliographical references.
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Optimizing ride matches for dynamic ride-sharing systemsWang, Xing 05 April 2013 (has links)
Ride-share systems, which aim to bring together travelers with similar itineraries and time schedules, may provide significant societal and environmental benefits by reducing the number of cars used for personal travel and improving the utilization of available seat capacity. Effective and efficient optimization technology that matches drivers and riders in real-time is one of the necessary components for a successful ride-share system. The research conducted in this dissertation formally defines dynamic or real-time ride-sharing, identifies optimization problems for finding best sets of ride-share matches in a number of operational scenarios, develops approaches for solving ride-share optimization problems, and tests the concepts via a simulation study of work trips in the Atlanta metropolitan area.
The first chapter introduces the motivation of the ride-sharing problem and briefly defines the dynamic ride-sharing system.
In Chapter 2, we systematically outline the optimization challenges that arise when developing technology to support ride-sharing and survey the related operations research models in academic literature.
In Chapter 3, we develop optimization-based approaches for finding ride-share matches in a standard problem setting, with the goal of minimizing the total system-wide vehicle miles incurred by system users. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules substantially improves the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers.
In Chapter 4, we consider a more sophisticated ride-share setting where participants may be unlikely to accept ride-share matches if they are not stable. Generically, a set of matches between riders and drivers is defined as stable if no rider and driver, currently matched to others, would prefer to be matched together. This notion of stability is similar to that of the stable marriage problem. We develop notions of stable ride-share matching in a variety of settings, and develop approaches for finding stable (or nearly-stable) solutions. Computational results are used to compare system performance under various levels of matching stability. A system with unstable matching assignments is simulated over two months in which participants are likely to reject the system's assignment if a private arrangement between individuals could bring better benefits. The simulation results indicate that the total savings generated by a ride-sharing system deteriorate with unstable matching assignments and that enforcing stability constraints in matching models is beneficial.
In Chapter 5, we consider another set of more sophisticated ride-share matching settings where participants are not assumed to accept each match to which they are assigned. In such settings, it may be useful to present users with a menu of possible ride-share matches from which they can choose. We develop models and solution approaches to jointly present multiple options to participants based on a complete bipartite graph structure. This research could serve as a building block for future work on the dynamic ride-sharing problem.
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Measuring facets of polyhedra to predict usefulness in branch-and-cut algorithmsHunsaker, Braden K. 01 December 2003 (has links)
No description available.
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Essays on financial dynamic optimization under uncertaintyHambusch, Gerhard. January 2008 (has links)
Thesis (Ph.D.)--University of Wyoming, 2008. / Title from PDF title page (viewed on August 5, 2009). Includes bibliographical references.
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Optimization of transition state structures using genetic algorithms /Bungay, Sharene D., January 2000 (has links)
Thesis (M.Sc.)--Memorial University of Newfoundland, 2000. / Bibliography: leaves 80-82.
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Deterministic approximations in stochastic programming with applications to a class of portfolio allocation problemsDokov, Steftcho Pentchev. January 2001 (has links)
Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.
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Hearing aid fitting with genetic algorithms /Durant, Eric Alan, Wakefield, Gregory H. January 2002 (has links)
Thesis (Ph. D.)--University of Michigan, 2002. / Includes bibliographical references. Also available on the Internet.
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Investigating the use of tabu search to find near-optimal solutions in multiclassifier systemsKorycinski, Donna Kay, January 2003 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.
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