Evaluation of competitiveness is the strategic choice for the logistics enterprise. In this paper a new framework of combinational evaluation methodology based on statistics is constructed. At first the Kendall coeffi...
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ISBN:
(纸本)9781424420124
Evaluation of competitiveness is the strategic choice for the logistics enterprise. In this paper a new framework of combinational evaluation methodology based on statistics is constructed. At first the Kendall coefficient of consistency is computed to identify whether the different single evaluation methods are compatible. A nonlinear program is constructed to determine the weight of different evaluation method result. The effect of the combinational method is determined with the index of MAPE and MSPE. Then competitiveness of logistics enterprise are evaluated with the combinational evaluation method. The evaluation index system is constructed. Composite index, TOPSIS, Efficiency coefficient method and Factor analysis are chosen to take evaluation. Based on above 4 single evaluation methods, combinational evaluation is constructed with the nonlinear program. The explorative results show that combinational evaluation method is a kind of good evaluation method.
In flight control, control allocation is used to distribute the total control command to each actuator when the number of actuators exceeds the number of controlled variables. A new optimal control allocation method b...
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ISBN:
(纸本)9781424439089
In flight control, control allocation is used to distribute the total control command to each actuator when the number of actuators exceeds the number of controlled variables. A new optimal control allocation method based on nonlinear compensation was proposed in this paper. The quadratic term and mutual-interference effects were introduced into control effectiveness matrix. The linear combination of control objective and error objective was selected as optimal target. Then the optimal control allocation problem of redundancy system was solved by transformed to nonlinear programming formulation. Comparison with other allocation method and control system simulation results show the proposed method has timing properties similar to the redistributed pseudo-inverse method and achieves the objective accurately and optimally.
To support the Air Force's Global Reach concept, a Common Aero Vehicle is being designed to support the Global Strike mission. "Waypoints" are specified for reconnaissance or multiple payload deployments...
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ISBN:
(纸本)9780877035435
To support the Air Force's Global Reach concept, a Common Aero Vehicle is being designed to support the Global Strike mission. "Waypoints" are specified for reconnaissance or multiple payload deployments and "no-fly zones" are specified for geopolitical restrictions or threat avoidance. Due to time critical targets and multiple scenario analysis, an autonomous solution is preferred over a time-intensive, manually iterative one. Thus, a real-time or near real-time autonomous trajectory optimization technique is presented to minimize the flight time, satisfy terminal and intermediate constraints, and remain within the specified vehicle heating and control limitations. This research uses the Hypersonic Cruise Vehicle (HCV) as a simplified two-dimensional platform to compute an optimal analytical solution. An up- and-coming numerical technique is a direct solution method involving discretization then dualization, with pseudospectral methods and nonlinear programming used to converge to the optimal solution. This numerical technique is first compared to the previously derived 2-D HCV analytical results to demonstrate convergence to the optimal solution. Then, the numerical approach is applied to the 3-D Common Aero Vehicle (CAV) as the test platform for the flat Earth three-dimensional reentry trajectory optimization problem. The culmination of this research is the verification of the optimality of this proposed numerical technique, as shown for both the two-dimensional and three-dimensional models. Additionally, user implementation strategies are presented to improve accuracy, enhance solution convergence, and facilitate autonomous implementation.
In this paper the problem of finding the maximum diameter of q equal non-overlapping circles on the surface of a sphere is considered. The packing problem resolution method proposed adopts a smoothing strategy using a...
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In this paper, we develop heuristics for finding good starting points when solving large-scale nonlinear constrained optimization problems (COPs). We focus on nonlinear programming (NLP) and mixed-integer NLP (MINLP) ...
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ISBN:
(纸本)9780769534404
In this paper, we develop heuristics for finding good starting points when solving large-scale nonlinear constrained optimization problems (COPs). We focus on nonlinear programming (NLP) and mixed-integer NLP (MINLP) problems with nonlinear non-convex objective and constraint functions. By exploiting the highly structured constraints in these problems, we first solve one or more simplified versions of the original COP, before generalizing the solutions found by interpolation or extrapolation to a good starting point. In our experimental evaluations of 190 NLP (resp., 52 MINLP) benchmark problems, our approach can solve 97.9% (resp., 71.2%) of the problems using significantly less iterations from our proposed starting points, as compared to 85.3% (resp., 462%) of the problems solvable by the best existing solvers from their default starting points.
The class of stochastic nonlinear programming (SNIP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications including those in the field of process systems engin...
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The class of stochastic nonlinear programming (SNIP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications including those in the field of process systems engineering. But despite the apparent importance of such problems, solution algorithms for these problems have found few applications due to severe computational and structural restrictions. To that effect, this work proposes a new algorithm for computationally efficient solution of the SNLP problems. Starting with the basic structure of traditional L-shaped method, the new algorithm called L-shaped BONUS incorporates reweighting scheme to ease computational load in the second stage recourse function calculation. The reweighting idea has been previously used successfully in optimization in BONUS, also an algorithm to solve SNLP problems. The proposed algorithm is analyzed using different case study problems including a blending problem relevant to process industry and a large scale novel sensor placement problem for water security networks. All problem results show considerable savings in computational time without compromising accuracy, the performance being better for Hammersley sequence sampling technique as compared to Monte Carlo sampling technique.
This paper presents a state of the art of actual achievements in time-domain system identification using fractional models. It starts with some general aspects on time and frequency-domain representations, time-domain...
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ISBN:
(纸本)9780791848067
This paper presents a state of the art of actual achievements in time-domain system identification using fractional models. It starts with some general aspects on time and frequency-domain representations, time-domain simulation, and stability of fractional models. Then, an overview on system identification methods using fractional models is presented. Both equation-error and output-error-based models are detailed. In the former models, prior knowledge is generally used to fix differentiation orders;model coefficients are estimated using least squares. The latter models allow simultaneous estimation of model's coefficients and differentiation orders, using non linear programming. A real thermal example is identified using a fractional model and compared to a rational one.
The multi-threshold-voltage CMOs (MTCMOS) technique is very effective for reducing leakage power. Previously, sleep transistors were connected the virtual ground lines to reduce the power consumption, and a Distribute...
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ISBN:
(纸本)9781424421664
The multi-threshold-voltage CMOs (MTCMOS) technique is very effective for reducing leakage power. Previously, sleep transistors were connected the virtual ground lines to reduce the power consumption, and a Distributed Sleep Transistor Network (DSTN) was proposed to reduce the instantaneous current. This paper presents a research on how to find the near optimal solution for the sleep transistor sizing problem in the DSTN structure. This paper adopts Lagrange Successive Over-Relaxation (SOR) iterative method which is frequently used in the optimization field. The method makes sure the Lagrange Multiplier satisfying the extreme conditions during the adjustment in each iteration, in order to find the near-optimum of the problem. Our experimental results are very exciting compared with the nonlinear programming.
This paper presents an application of neurobiological motor principles to the control of humanoid robot reaching movements. The model is mainly based on the hypotheses that the energy of motoneurons;signals is continu...
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ISBN:
(纸本)9781424428823
This paper presents an application of neurobiological motor principles to the control of humanoid robot reaching movements. The model is mainly based on the hypotheses that the energy of motoneurons;signals is continuously minimized along the motion and that dynamic and static efforts are processed separately. This paradigm is used to control the robot HRP2 by considering a dynamic model of the arm including, for each degree of freedom, two second order low-pass filters modeling the neuromuscular system defined by a pair of antagonist muscles. The optimal control problem is solved as a nonlinear programming problem by using a direct transcription method coupled with the optimization software Ipopt. This approach allows to generate realistic movements with anthropomorphic features such as quasi-rectilinear trajectories and bell-shaped velocity.
This paper addresses the congestion management problem avoiding offline transmission capacity limits related to stability. These limits on line power flows are replaced by optimal power flow-related constraints that e...
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ISBN:
(纸本)9781424419050
This paper addresses the congestion management problem avoiding offline transmission capacity limits related to stability. These limits on line power flows are replaced by optimal power flow-related constraints that ensure an appropriate level of security, mainly targeting voltage instabilities, which are the most common source of stability problems. Results from an illustrative case study based on the IEEE 24-bus Reliability Test System are analyzed. Conclusions are duly drawn.
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