Numerical test results are presented for solving smooth nonlinear programming problems with a large number of constraints, but a moderate number of variables. The active set method proceeds from a given bound for the ...
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Numerical test results are presented for solving smooth nonlinear programming problems with a large number of constraints, but a moderate number of variables. The active set method proceeds from a given bound for the maximum number of expected active constraints at an optimal solution, which must be less than the total number of constraints. A quadraticprogramming subproblem is generated with a reduced number of linear constraints from the so-called working set, which is internally changed from one iterate to the next. Only for active constraints, i.e., a certain subset of the working set, flew gradient values must be computed. The line search is adapted to avoid too many active constraints which do not fit into the working set. The active set strategy is an extension of an algorithm described earlier by the author together with a rigorous convergence proof. Numerical results for some simple academic test problems show that nonlinear programs with up to 200,000,000 nonlinear constraints are efficiently solved on a standard PC. (C) 2009 IMACS. Published by Elsevier B.V. All rights reserved.
The article focuses on a study on the development of a linear feedback guidance scheme for-low thrust Earth-orbit transfers that involve many orbital revolutions. The key concept of the proposed guidance scheme is cit...
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The article focuses on a study on the development of a linear feedback guidance scheme for-low thrust Earth-orbit transfers that involve many orbital revolutions. The key concept of the proposed guidance scheme is cited. It notes that the study used the parameterized control law in both optimization and guidance. According to the author, the scheme possesses near-optimal performance because the optimal trajectory and control can tracked by means of space vehicles.
We consider the downlink of a multiuser system equipped with multiple antennas transmitting to multiple single-antenna mobile receivers. Particle swarm optimisation (PSO) is invoked to solve the constrained nonlinear ...
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We consider the downlink of a multiuser system equipped with multiple antennas transmitting to multiple single-antenna mobile receivers. Particle swarm optimisation (PSO) is invoked to solve the constrained nonlinear optimisation problem for the minimum bit error rate (MBER) multiuser transmitter (MUT). The proposed PSO aided symbol-specific MBER-MUT and average MBER-MUT schemes provide improved performance in comparison to the conventional minimum mean-square-error MUT scheme, while imposing a reduced complexity compared to the state-of-the-art sequential quadratic programming based symbol-specific MBER-MUT and average MBER-MUT schemes, respectively.
This research considered the multi-objective shape optimisation of an automotive universal joint. Optimisation was conducted at the component level and assembly level using a weighted sum of three objective functions:...
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This research considered the multi-objective shape optimisation of an automotive universal joint. Optimisation was conducted at the component level and assembly level using a weighted sum of three objective functions: part volume, adjoining joint angle and machining cost. All measures of performance were competing objective functions (increasing joint angle required a corresponding increase in volume and cost). Results of the component level optimisation overestimated potential improvements when compared to the assembly level optimisation. Furthermore, optimum designs created at the component level were infeasible in the assembly level domain, thereby emphasising the importance of conducting design optimisation at the assembly level.
We implement and test a globally convergent sequential approximate optimization algorithm based on (convexified) diagonal quadratic approximations. The algorithm resides in the class of globally convergent optimizatio...
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We implement and test a globally convergent sequential approximate optimization algorithm based on (convexified) diagonal quadratic approximations. The algorithm resides in the class of globally convergent optimization methods based on conservative convex separable approximations developed by Svanberg. At the start of each outer iteration, the initial curvatures of the diagonal quadratic approximations are estimated using historic objective and/or constraint function value information, or by building the diagonal quadratic approximation to the reciprocal approximation at the current iterate. During inner iterations, these curvatures are increased if no feasible descent step can be made. Although this conditional enforcement of conservatism on the subproblems is a relaxation of the strict conservatism enforced by Svanberg, global convergence is still inherited from the conservative convex separable approximations framework developed by Svanberg. A numerical comparison with the globally convergent version of the method of moving asymptotes and the nonconservative variants of both our algorithm and method of moving asymptotes is made.
Future solar sail and solar power satellite missions will consider using centrifugal forces for deployment and stabilization. Some of the main advantages with spin deployment are that the significant forces are in the...
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Future solar sail and solar power satellite missions will consider using centrifugal forces for deployment and stabilization. Some of the main advantages with spin deployment are that the significant forces are in the plane of rotation, and a relatively simple control can be used and the tension in the membrane or web can be adjusted by the spin rate. Existing control strategies seem to either consume excessive energy or cause oscillations. In this study, control laws are derived from the solution to relevant optimal control problems and existing controls. The derived control laws are used in deployment simulations with both simple analytical three-degree-of-freedom models and a fully-three-dimensional finite element model. The results indicate that the derived control laws can be used to minimize the energy consumption and oscillations as for an optimal control, yet retain the simplicity of previous control laws.
Positioning accuracy in satellite navigation systems depends on time-delay estimation (TDE) between satellite transmitted codes and local receiver replicas. This paper explores the fundamental limits of TDE accuracy o...
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Positioning accuracy in satellite navigation systems depends on time-delay estimation (TDE) between satellite transmitted codes and local receiver replicas. This paper explores the fundamental limits of TDE accuracy of spread spectrum signals making use of estimation theory. In particular, this contribution derives some criteria to improve positioning accuracy in the additive white Gaussian noise (multipath-free) scenario, focusing on the (satellite) transmitter side of a direct sequence spread spectrum (DS-SS) system. Three different solutions based on the minimization of the variance of the TDE are presented. The first method derives a design criterion for the shaping pulse format. The second approach outlines a method to design binary pseudo-random spreading sequences. The third solution considers a joint shaping pulse-spreading code optimization to derive band-limited, non-binary spreading waveforms. Performance of the proposed solutions is compared with that of existing DS-SS signals for current satellite positioning systems. Possible countermeasures to the effects of multipath propagation are also discussed.
The increasing costs of fuel and operation of thermal power generating units warrant development of optimization methodologies for economic dispatch (ED) problems. Optimization methodologies that are based on meta-heu...
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The increasing costs of fuel and operation of thermal power generating units warrant development of optimization methodologies for economic dispatch (ED) problems. Optimization methodologies that are based on meta-heuristic procedures could assist power generation policy analysts to achieve the goal of minimizing the generation costs. In this context, the objective of this study is to present a novel approach based on harmony search (HS) algorithm for solving ED problems, aiming to provide a practical alternative for conventional methods. To demonstrate the efficiency and applicability of the proposed method and for the purposes of comparison. various types of ED problems are examined. The results of this study show that the new proposed approach is able to find more economical loads than those determined by other methods. (C) 2009 Elsevier Ltd. All rights reserved.
In this paper, we focus on the design of a fuel-optimal maneuver strategy to reconfigure satellite formation using a low-thrust propulsion system. We cast it as an optimization problem with a desired final satellite f...
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In this paper, we focus on the design of a fuel-optimal maneuver strategy to reconfigure satellite formation using a low-thrust propulsion system. We cast it as an optimization problem with a desired final satellite formation configuration subject to collision avoidance constraints on the paths of the chief and all deputy satellites. The satellite terminal orbit states corresponding to this desired formation configuration are ensured by imposing an energy-matching condition and final geometry configuration constraints in the problem formulation. In addition, we adopt our recently developed relative satellite kinematics model to accurately describe relative satellite orbit geometry in the presence of J(2) effects. The resulting nonlinear optimal control problem is converted into a nonlinear programming problem by the application of the Legendre pseudospectral method and is then solved by using a sparse nonlinear optimization software named TOMLAB/SNOPT. Simulation results demonstrate the efficiency of our proposed method in designing fuel-optimal maneuvers for a wide class of satellite formation problems.
A proper selection of a work-in-process (WIP) inventory level has great impact onto the productivity of wafer fabrication processes, which can be properly used to trigger the decision of when to release specific wafer...
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A proper selection of a work-in-process (WIP) inventory level has great impact onto the productivity of wafer fabrication processes, which can be properly used to trigger the decision of when to release specific wafer lots. However, the selection of ail optimal WIP is always a tradeoff amongst the throughput rate, the cycle time and the standard deviation of the cycle time. This study focused on finding,in optimal WIP value of wafer fabrication processes by developing ail algorithm integrating ail artificial neural network (ANN) and the sequential quadratic programming (SQP) method. With this approach, it offered ail effective and systematic way to identify ail optimal WIP level. Hence, the efficiency of finding the optimal WIP level was greatly improved. (C) 2008 Elsevier Ltd. All rights reserved.
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