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41 
Optimal transmitter placement in wireless mesh networksNicholas, Paul J. January 2009 (has links) (PDF)
Thesis (M.S. in Operations Research)Naval Postgraduate School, June 2009. / Thesis Advisor(s): Alderson, David. "June 2009." Author(s) subject terms: Wireless Mesh Networks, Humanitarian Assistance, Disaster Relief, Distributed Operations, Enhanced Company Operations, Network Design, Nonlinear Programming, Terrain Integrated Rough Earth Model, TIREM, Hata COST231, Simultaneous Routing and Resource Allocation, Dividing Rectangles, DIRECT, Access Points, Access Point Placement, C++ Description based on title screen as viewed on July 13, 2009. Includes bibliographical references (p. 119122). Also available in print.

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Control and Optimization of Track Coverage in Underwater Sensor NetworksBaumgartner, Kelli A. Crews. January 2007 (has links)
Thesis (Ph. D.)Duke University, 2007.

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Analyse und Anwendungen von Quotientenprogrammen e. Beitr. zur Planung mit Hilfe d. nichtlinearen Programmierung /Schaible, Siegfried. January 1978 (has links)
HabilitationsschriftCologne, 1977. / Includes bibliographical references (p. [238]259).

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OQGRG a multistart algorithm for global solution of nonlinear and mixed integer programs /Ugray, Zsolt Gyula. January 2001 (has links) (PDF)
Thesis (Ph. D.)University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI Company.

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Convergence of a gradient projection methodJanuary 1982 (has links)
Eli M. Gafni, Dimitri P. Bertsekas. / "May 1982" / Bibliography: leaf 12. / "Grant NSF ENG79106332"

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Location of stable and unstable equilibrium configurations using a model trust region quasiNewton method and tunnellingKwok, Heeyuen Herbert January 1983 (has links)
A hybrid method consists of a quasiNewton method and a homotopy method for locating multiple equilibrium configurations has been proposed recently. The hybrid method combined the efficiency of a quasiNewton method capable of locating stable and unstable equilibrium solutions with a robust homotopy method capable of tracking equilibrium paths with turning points and exploiting sparsity of the Jacobian matrix at the same time. A quasiNewton method in conjunction with a deflation technique is proposed here as an alternative to the hybrid method. The proposed method not only exploits sparsity and symmetry, but also represents an improvement in efficiency. Limit points and nearby equilibrium solutions, either stable or unstable, can be accurately located with the use of a modified pseudoinverse based on the singular value decomposition. This pseudoinverse modification destroys the Jacobian matrix sparsity, but is invoked only rarely (at limit arid bifurcation points where the Jacobian matrix is singular). / M.S.

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QuasiNewton algorithms for large scale nonlinear systemsVandenBrink, Dennis Jay January 1983 (has links)
In this work, an evaluation of a number of quasiNewton algorithms and strategies for sparse, symmetric Hessian matrices was performed. It was shown how these quasiNewton algorithms could be applied to the unconstrained minimization of a nonlinear function as well as a nonlinear least squares approach to solving a system of nonlinear equations. The best of these algorithms were evaluated for a problem with a fairly large number of degrees of freedom with a large load increment. From this study it is concluded that the proposed quasiNewton method with the double dogleg strategy and an automatic control on Hessian evaluations is the best algorithm for all of the problems considered in this investigation. The algorithm had no difficulty converging to solutions regardless of the size of the model and regardless of the size of the load or time step. The advantage of being able to take large load or time steps may lie in those problems which involve the location of critical points (limit or bifurcation points) of structures with minimal computational effort. All the algorithms which utilized the double dogleg strategy were consistently better able to converge to the solution  a clear validation of the globally convergent property of the double dogleg strategy. Finally, the usefulness of the double dogleg strategy in solving a system of nonlinear equations via the nonlinear least squares approach and in locating multiple equilibrium configurations using deflation speaks for the versatility of the proposed algorithm.
In conclusion, the quasiNewton algorithm proposed in this dissertation is both robust and efficient for small as well as large scale problems of matrices are exploited. Because sparsity and symmetry the algorithm does not place unreasonable demands on core storage requirements. Furthermore, using the deflation technique with tunneling the algorithm can be extremely useful for postbuckling response studies of structures involving many stable and unstable branches. / Ph. D.

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Global Optimization of Nonconvex Factorable Programs with Applications to Engineering Design ProblemsWang, Hongjie 12 June 1998 (has links)
The primary objective of this thesis is to develop and implement a global optimization algorithm to solve a class of nonconvex programming problems, and to test it using a collection of engineering design problem applications.The class of problems we consider involves the optimization of a general nonconvex factorable objective function over a feasible region that is restricted by a set of constraints, each of which is defined in terms of nonconvex factorable functions. Such problems find widespread applications in production planning, location and allocation, chemical process design and control, VLSI chip design, and numerous engineering design problems. This thesis offers a first comprehensive methodological development and implementation for determining a global optimal solution to such factorable programming problems. To solve this class of problems, we propose a branchandbound approach based on linear programming (LP) relaxations generated through various approximation schemes that utilize, for example, the MeanValue Theorem and Chebyshev interpolation polynomials, coordinated with a {em ReformulationLinearization Technique} (RLT). The initial stage of the lower bounding step generates a tight, nonconvex polynomial programming relaxation for the given problem. Subsequently, an LP relaxation is constructed for the resulting polynomial program via a suitable RLT procedure. The underlying motivation for these two steps is to generate a tight outer approximation of the convex envelope of the objective function over the convex hull of the feasible region. The bounding step is thenintegrated into a general branchandbound framework. The construction of the bounding polynomials and the node partitioning schemes are specially designed so that the gaps resulting from these two levels of approximations approach zero in the limit, thereby ensuring convergence to a global optimum. Various implementation issues regarding the formulation of such tight bounding problems using both polynomial approximations and RLT constructs are discussed. Different practical strategies and guidelines relating to the design of the algorithm are presented within a general theoretical framework so that users can customize a suitable approach that takes advantage of any inherent special structures that their problems might possess. The algorithm is implemented in C++, an objectoriented programming language. The class modules developed for the software perform various functions that are useful not only for the proposed algorithm, but that can be readily extended and incorporated into other RLT based applications as well. Computational results are reported on a set of fifteen engineering process control and design test problems from various sources in the literature. It is shown that, for all the test problems, a very competitive computational performance is obtained. In most cases, the LP solution obtained for the initial node itself provides a very tight lower bound. Furthermore, for nine of these fifteen problems, the application of a local search heuristic based on initializing the nonlinear programming solver MINOS at the node zero LP solution produced the actual global optimum. Moreover, in finding a global optimum, our algorithm discovered better solutions than the ones previously reported in the literature for two of these test instances. / Master of Science

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Iterative nonlinear goal programming and application to production planning problemsRaju, Kosuri S. January 1978 (has links)
Call number: LD2668 .T4 1978 R36 / Master of Science

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A comparative study of nonlinear programming routines on the microcomputer versus the large computerHwang, Frank P. January 1984 (has links)
Call number: LD2668 .T4 1984 H92 / Master of Science

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