This paper introduces a robust searching hybrid differential evolution (RSHDE) method to solve the optimal feeder reconfiguration for power loss reduction. The feeder reconfiguration of distribution systems is to reco...
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This paper introduces a robust searching hybrid differential evolution (RSHDE) method to solve the optimal feeder reconfiguration for power loss reduction. The feeder reconfiguration of distribution systems is to recognize beneficially load transfers so that the objective function composed of power losses is minimized and the prescribed voltage limits are satisfied. Mathematically, the problem of this research is a nonlinear programming problem with integer variables. This paper presents a new approach, which uses the RSHDE algorithm with integer variables to solve the problem. Owing to handle the integer variables, the HDE may fail to find the initial search direction for large-scale integer system. This is because the HDE applies a random search at its initial stages. Therefore, two new schemes, the multidirection search scheme and the search space reduction scheme, are embeded into the HDE. These two schemes are used to enhance the search ability before performing the initialization step of the solution process. One three-feeder distribution system from the literature and one practical distribution network of Taiwan Power Company (TPC) are used to exemplify the performance of the proposed method. Moreover, the previous HDE, simulated annealing (SA) and genetic algorithms (GA) methods are also applied to the same example systems for the purpose of comparison. Numerical results show that the proposed method is better than the other methods.
Eigenvalues play an important role in many fields of applied mathematics to engineering. For some applications it may be desirable to calculate the variables of a model in order to optimize an objective function and/o...
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Eigenvalues play an important role in many fields of applied mathematics to engineering. For some applications it may be desirable to calculate the variables of a model in order to optimize an objective function and/or to verify constraints that involve the eigenvalues of a certain matrix. In general the elements of such a matrix depend nonlinearly on the optimization variables. Despite its potential to address diverse chemical engineering problems, eigenvalue optimization techniques have not been extensively used in the Process Systems Engineering discipline. The objectives of this contribution are to review most relevant topics on eigenvalue optimization and to present formulations and solution strategies to practically address eigenvalue optimization problems in the field of chemical engineering. In order to illustrate the ideas, several small size applications, which have to do with the analysis and control of nonlinear dynamic systems, are developed. Other potential applications and future lines of research are also suggested. (c) 2007 Elsevier B.V. All rights reserved.
In this paper, two auxiliary functions for global optimization are proposed. These two auxiliary functions possess all characters of tunnelling functions and filled functions under certain general assumptions. Thus, t...
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In this paper, two auxiliary functions for global optimization are proposed. These two auxiliary functions possess all characters of tunnelling functions and filled functions under certain general assumptions. Thus, they can be considered as the unification of filled function and tunnelling function. Moreover, the process of tunneling or filling for global optimization can be unified as the minimization of such auxiliary functions. Result of numerical experiments shows that such two auxiliary functions are effective.
In this paper, we propose a recurrent neural network model for solving a class of monotone variational inequalities problem with linear constraints. The neural network is stable in the sense of Lyapunov and globally c...
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In this paper, we propose a recurrent neural network model for solving a class of monotone variational inequalities problem with linear constraints. The neural network is stable in the sense of Lyapunov and globally convergent to an optimal solution. Compared with the existing convergence results, the present proof do not require Lipschitz continuity condition on the objective function. This neural network model has no adjustable parameter thus its structure is very simple. Variational inequalities problem with general set of constraints plus a general form of the complementarity problems are solved using the proposed neural networks. Some examples demonstrated to show the applicability of the proposed neural networks to solve various nonlinear optimization problems numerically. (C) 2007 Elsevier Inc. All rights reserved.
In this paper, we establish a strong duality theorem for a pair of Mond-Weir type second-order nondifferentiable symmetric dual problems. This removes certain inconsistencies in some of the earlier results.
In this paper, we establish a strong duality theorem for a pair of Mond-Weir type second-order nondifferentiable symmetric dual problems. This removes certain inconsistencies in some of the earlier results.
General two-dimensional fluid dynamics problems in which the desired complex-valued flow potential on the boundary of the flow region satisfies nonlinear boundary conditions are discussed. A method was proposed in for...
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General two-dimensional fluid dynamics problems in which the desired complex-valued flow potential on the boundary of the flow region satisfies nonlinear boundary conditions are discussed. A method was proposed in for specially choosing unknowns and desired functions such that the image of D is known in the domain of the new variables to analyze the well-posedness of such problems. Without loss of generality, the flow domain D can be assumed to be the upper half-plane Imz ≤0, which is obtained by a conformal mapping that does not change the properties of the coefficients in different equations.
THE determination of optimal aircraft trajectories has been of considerable interest to aircraft dynamicists for almost 50 years. The complexity of aircraft dynamics, in general, requires the separation of the guidanc...
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THE determination of optimal aircraft trajectories has been of considerable interest to aircraft dynamicists for almost 50 years. The complexity of aircraft dynamics, in general, requires the separation of the guidance and control design into inner and outer loops. The outer loop is driven by the navigation requirements. Typically, aircraft point-mass models are used for aircraft trajectory optimization when some aircraft performance parameters, such as lift, drag, and thrust need to be calculated. Other approaches that have been used for aircraft navigation around terrain and obstacles are often based only on kinematic considerations.
Recent research has shown that the load flow equations describing the steady-state conditions in a radial network can be formulated as a second-order cone program and solved using polynomial-time interior point method...
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Recent research has shown that the load flow equations describing the steady-state conditions in a radial network can be formulated as a second-order cone program and solved using polynomial-time interior point methods. This paper extends the conic formulation to meshed networks by including a trigonometric functional constraint for the voltage angle spread on each line in the network. In particular, it is shown that the load How solution of a meshed network can be obtained from a sequence of conic programming solutions. The proposed formulation and iterative procedure are validated by comparing with the Newton-Raphson solution of the standard power flow model. Testing is reported on seven networks. The proposed format of equations opens the door for new implementations of energy management system functions based on efficient and numerically robust conic quadratic optimization methods.
PTIMAL low-thrust interplanetary transfers in the heliocentric frame have been studied in many documented articles in which the planetary escape and capture maneuvers were not addressed. For example, [1-4] demonstrate...
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PTIMAL low-thrust interplanetary transfers in the heliocentric frame have been studied in many documented articles in which the planetary escape and capture maneuvers were not addressed. For example, [1-4] demonstrated different methods to find optimum steering programs for heliocentric orbital transfers. Moreover, a number of state-of-the-art low-thrust trajectory optimization tools are also available for mission designers. The Jet Propulsion Laboratory (JPL) developed the well-known SEPTOP and VARITOP [5] (SEPTOP's predecessor) programs that have been used for decades. More recently, JPL has demonstrated devotion to developing new low-thrust programs such as MYSTIC [6] and MALTO [7], which are more sophisticated and capable of designing complicated low-thrust trajectories. On the other hand, optimizing low-thrust planetocentric escape and capture trajectories has also been studied (see [8-11]). These prior efforts and studies reveal that mission designers are interested in low-thrust transfers from a low-Earth orbit (LEO) to a low-planet orbit. However, the literature dealing with optimizing the entire mission, including both heliocentric and planetocentric transfer trajectories, still appears to be somewhat limited. The most commonly used method is the patched-conic approximation, which was used by Melbourne and Sauer [12] in the 1960s. The interplanetary leg and planetocentric spirals are optimized separately and then patched together. Currently, this approximation *** still in wide use by mission designers.
A nonsmooth PGD scheme for minimizing a nonsmooth convex function is presented. In the parallelization step of the algorithm, a method due to Pang, Han and Pangaraj (1991), [7], is employed to solve a subproblem for c...
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A nonsmooth PGD scheme for minimizing a nonsmooth convex function is presented. In the parallelization step of the algorithm, a method due to Pang, Han and Pangaraj (1991), [7], is employed to solve a subproblem for constructing search directions. The convergence analysis is given as well.
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