作者：
Tran, AVTucker, RSBoland, NLUniv Melbourne
ARC Special Res Ctr Ultra Broadband Informat Netw Melbourne Vic 3010 Australia Univ Melbourne
Australian Photon Cooperat Res Ctr Photon Res Lab Dept Elect & Elect Engn Melbourne Vic 3010 Australia Univ Melbourne
Dept Math & Stat Melbourne Vic 3010 Australia
This paper presents two new amplifier placement methods to minimize the number of amplifiers in metropolitan wavelength-division-multiplexing (WDM) rings based on integer programming techniques. The first method descr...
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This paper presents two new amplifier placement methods to minimize the number of amplifiers in metropolitan wavelength-division-multiplexing (WDM) rings based on integer programming techniques. The first method describes the amplifier placement problem exactly and uses a nonlinear programming solver to obtain a solution. The second method approximates some requirements in the problem and employs a linear programming solver to derive the amplifier placement solution. A new amplifier placement method for self-healing WDM rings is also reported in this paper. The new method is based on iteratively solving an amplifier placement problem for a ring network under different link failure scenarios. The solution provides a minimum number of amplifiers required to operate the self-healing ring under a normal or any single-link or single-node failure conditions.
Process uncertainty is almost always an issue during the design of chemical processes (CP). In the open literature it has been shown that consideration of process uncertainties in optimal design necessitates the incor...
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Process uncertainty is almost always an issue during the design of chemical processes (CP). In the open literature it has been shown that consideration of process uncertainties in optimal design necessitates the incorporation of process flexibility. Such an optimal design can presumably operate reliably in the presence of process and modeling uncertainty. Halemane and Grossmann (1983) introduced a feasibility function for evaluating CP flexibility. They also formulated a two-stage optimization problem for estimating the optimal design margins. These formulations, however, are based implicitly on the assumption that during the operation stage, uncertain parameters can be determined with enough precision. This assumption is rather restrictive and is often not met in practice. When available experimental information at the operation stage does not allow a more precise estimate of some of the uncertain parameters, new formulations of the flexibility condition and the optimization problem under uncertainty are needed. In this article, we propose such formulations, followed by some computational experiments.
This paper pursues a numerical approach to the solution of the contact problem of a rigid punch on an incompressible half-plane, subjected to a shearing force together with a normal force which may be offset from the ...
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This paper pursues a numerical approach to the solution of the contact problem of a rigid punch on an incompressible half-plane, subjected to a shearing force together with a normal force which may be offset from the centerline of the punch. A piecewise-linear representation of the shear tractions is employed and quadratic programming techniques are used to solve the problem. This method enables an arbitrary load history to be followed. Results are presented which show excellent agreement with other solutions to the special cases of monotonic and steady-state cyclic loading. It is shown that the traction distribution reaches a steady-state cycle after only a few cycles of loading. The existence of an interesting stick-slip regime, where a central zone of slip is bordered by two stick regions is highlighted.
Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity! One way of achieving near-optimum performance without the complexit...
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ISBN:
(纸本)0769510620
Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity! One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.
We propose a class of satellite constellations that can act as interferometric observatories in Earth orbit. The satellite constellation is capable of forming high-resolution images in timescales of a few hours withou...
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We propose a class of satellite constellations that can act as interferometric observatories in Earth orbit. The satellite constellation is capable of forming high-resolution images in timescales of a few hours without the need for active control beyond that needed for corrective maneuvers. First, we discuss the requirements to achieve these imaging goals. Next, we define a class of constellations that can achieve these goals. An optimization procedure is also defined that supplies m pixels of resolution with a minimum number of satellites. For the example considered, this procedure results in an observatory that is within 0-2 satellites from a lower bound of sq rt m satellites. The zonal J2 effect is used to scan the observatory across the celestial sphere. Finally, we discuss the practical implementation of these observatories.
A Chebyshev pseudospectral method has been used to obtain optimaltrajectories for tethered planetary capture missions. Maximum tether reel rates and tether mass arecalculated for mass ratios be-, tween 5 and 15 of the...
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A Chebyshev pseudospectral method has been used to obtain optimaltrajectories for tethered planetary capture missions. Maximum tether reel rates and tether mass arecalculated for mass ratios be-, tween 5 and 15 of the main spacecraft mass to payload *** results show that it possible to transfer a payload from a hyperbolic orbit to anelliptical orbit by the use of practical tether reel rates (10-20 m/s) at both Venus and *** tether mass required to sustain the tension forces is between 43 and 55% of the propellant massneeded to perform a similar maneuver using rocket propulsion. It is apparent that tethers provide anefficient means for performing controlled planetary capture maneuvers and may be an important toolfor future space exploration.
We extend the convergence analysis of a smoothing method [M. Fukushima and J.-S. Pang (2000). Convergence of a smoothing continuation method for mathematical programs with complementarity constraints. In: M. Thera and...
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We extend the convergence analysis of a smoothing method [M. Fukushima and J.-S. Pang (2000). Convergence of a smoothing continuation method for mathematical programs with complementarity constraints. In: M. Thera and R. Tichatschke (Eds.), Ill-posed Variational Problems and Regularization Techniques, pp. 99-110. Springer, Berlin/Heidelberg.] to a general class of smoothing functions and show that a weak second-order necessary optimality condition holds at the limit point of a sequence of stationary points found by the smoothing method. We also show that convergence and stability results in [S. Scholtes (2001). Convergence properties of a regularization scheme for mathematical programs with complementarity constraints. SIAM J. Optim., 11, 918-936.] hold for a relaxation problem suggested by Scholtes [S. Scholtes (2003). Private communications.] using a class of smoothing functions. In addition, the relationship between two technical, yet critical, concepts in [M. Fukushima and J.-S. Pang (2000). Convergence of a smoothing continuation method for mathematical programs with complementarity constraints. In: M. Thera and R. Tichatschke (Eds.), Ill-posed Variational Problems and Regularization Techniques, pp. 99-110. Springer, Berlin/Heidelberg;S. Scholtes (2001). Convergence properties of a regularization scheme for mathematical programs with complementarity constraints. SIAM J. Optim., 11, 918-936.] for the convergence analysis of the smoothing and regularization methods is discussed and a counter-example is provided to show that the stability result in [S. Scholtes (2001). Convergence properties of a regularization scheme for mathematical programs with complementarity constraints. SIAM J. Optim., 11, 918-936.] cannot be extended to a weaker regularization.
Maxiumum-Range trajectories in the vertical plane are extremely important for gliders that possess a limited amount of initial energy. Also, every airplane becomes a glider if the engine is turned off on purpose or if...
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Maxiumum-Range trajectories in the vertical plane are extremely important for gliders that possess a limited amount of initial energy. Also, every airplane becomes a glider if the engine is turned off on purpose or if the engine fails because of fuel shortage or technical reasons. When speeds were relatively low, performance optimization of aircraft was studied on a steady-state basis.' The best range glide in a steady-state situation is well known. However, such a result ignores the boundary conditions of the problem. With the development of high-performance aircraft and air-launched gliding vehicles, the dynamic effects could no longer be neglected.
The minimization of network flow problems with linear/nonlinear side constraints can be performed by minimizing an augmented Lagrangian function, including only the side constraints. This method gives rise to an algor...
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The minimization of network flow problems with linear/nonlinear side constraints can be performed by minimizing an augmented Lagrangian function, including only the side constraints. This method gives rise to an algorithm that combines first- and superlinear-order estimators of the multipliers of the side constraints. The code PFNRN03 is the implementation of this algorithm in Fortran 77. The main aim of this work is to compare the efficiency of this code on two sets of (industrial, artificial) test problems with that of the general-purpose solvers MINOS, SNOPT, LANCELOT and LOQO. Numerical results of these four codes are obtained by the NEOS server with AMPL input. The comparison indicates that PFNRN03 may be effective on current large-scale network flow problems with nonlinear side constraints.
An NGTN method was proposed for solving large-scale sparse nonlinear programming (NLP) problems. This is a hybrid method of a truncated Newton direction and a modified negative gradient direction, which is suitable fo...
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An NGTN method was proposed for solving large-scale sparse nonlinear programming (NLP) problems. This is a hybrid method of a truncated Newton direction and a modified negative gradient direction, which is suitable for handling sparse data structure and pos sesses Q-quadratic convergence rate. The global convergence of this new method is proved, the convergence rate is further analysed, and the detailed implementation is discussed in this paper. Some numerical tests for solving truss optimization and large sparse problems are reported. The theoretical and numerical results show that the new method is efficient for solving large-scale sparse NLP problems.
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