Here we present a primal-dual interior point nonmonotone line search filter method for nonlinear programming. The filter relies on three measures, the feasibility, the centrality and the optimality presented in the op...
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Here we present a primal-dual interior point nonmonotone line search filter method for nonlinear programming. The filter relies on three measures, the feasibility, the centrality and the optimality presented in the optimality conditions, and considers relaxed acceptability criteria for the step size and includes a feasibility restoration phase. Evaluation of the method has, until now, been made on small problems and a comparison is provided with a merit function approach.
Recently, a new Pattern Recognition technique based oil straight line segments (SLSs) was presented. The key issue in this new technique is to find a function based on distances between points and two sets of SLSs tha...
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ISBN:
(纸本)9780769533582
Recently, a new Pattern Recognition technique based oil straight line segments (SLSs) was presented. The key issue in this new technique is to find a function based on distances between points and two sets of SLSs that minimizes a certain error or risk criterion. An algorithm for solving this optimization problem is called training algorithm. Although this technique seems to be very promising, the first presented training algorithm is based on a heuristic. In fact, the search for this best function is a hard nonlinear optimization problem. In this paper we present a new and improved training algorithm for the SLS technique based on gradient descent optimization method. We have applied this new training algorithm to artificial and public data sets and their results confirm the improvement of this methodology.
This paper presents a method to determine the rough shape of an object. This is a step in the development of a "One Click Grasping Tool", a grasping tool of everyday-life objects for an assistant robot dedic...
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ISBN:
(纸本)9781424420575
This paper presents a method to determine the rough shape of an object. This is a step in the development of a "One Click Grasping Tool", a grasping tool of everyday-life objects for an assistant robot dedicated to elderly or disabled. The goal is to determine the quadric that approximates at best the shape of an unknown object using multi-view measurements. Non-linear optimization techniques are considered to achieve this goal. Since multiple views are necessary, an active vision process is considered in order to minimize the uncertainty on the estimated parameters and determine the next best view. Finally, results that show the validity of the approach are presented.
Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is pr...
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Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.
In this paper I describe a new and exciting application of optimization technology. The problem is to design a space telescope capable of imaging Earth-like planets around nearby stars. Because of limitations inherent...
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In this paper I describe a new and exciting application of optimization technology. The problem is to design a space telescope capable of imaging Earth-like planets around nearby stars. Because of limitations inherent in the wave nature of light, the design problem is one of diffraction control so as to provide the extremely high contrast needed to image a faint planet positioned very close to its much brighter star. I will describe the mathematics behind the diffraction control problem and explain how modern optimization tools were able to provide unexpected solutions that actually changed NASA's approach to this problem.
The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases a...
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The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration - the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.
This paper presents an outer-approximation algorithm to address a generalized maximum entropy sampling (GMES) problem that determines a set of measurement locations providing the largest entropy reduction. A new mixed...
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ISBN:
(纸本)9781424420780
This paper presents an outer-approximation algorithm to address a generalized maximum entropy sampling (GMES) problem that determines a set of measurement locations providing the largest entropy reduction. A new mixed-integer semidefinite program (MISDP) formulation is proposed to handle a GMES problem with a jointly Gaussian distribution over the search space. This formulation employs binary variables to indicate if the corresponding measurement location is selected, and exploits the linear equivalent form of a bilinear term involving binary variables to ensure convexity of the objective function and linearity of the constraint functions. An outer-approximation algorithm is developed for this formulation that obtains the optimal solution by solving a sequence of mixed-integer linear program. Numerical experiments are presented to verify the solution optimality and the computational effectiveness of the proposed algorithm by comparing it with an existing branch-and-bound method that utilizes nonlinear programming relaxation. Sensor selection for best tracking of a moving target under a communication budget constraint is specifically considered to validate the superiority of the suggested algorithm in handling quadratic constraints.
In this paper, we suggest a new optimization method by using grey area relational grade combined with nonlinear programming (abbreviated to NLP) method for GM(1,1) model's parameters, we introduce the grey area re...
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ISBN:
(纸本)9781424418183
In this paper, we suggest a new optimization method by using grey area relational grade combined with nonlinear programming (abbreviated to NLP) method for GM(1,1) model's parameters, we introduce the grey area relational grade to establish a NLP optimization parameters model for a GM(1, 1) model that has been established, by using mathematical software LINGO 10.0 for its optimal solution. By a lot of data's analysis, we conclude the new method is effective and feasible for the GM(1, 1) models that have been established by using any other methods.
We consider the ensemble of codes formed by a serial concatenation of a repetition code with two accumulators through uniform random interleavers. For this ensemble, asymptotic expressions for the normalized minimum t...
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ISBN:
(纸本)9781424429257
We consider the ensemble of codes formed by a serial concatenation of a repetition code with two accumulators through uniform random interleavers. For this ensemble, asymptotic expressions for the normalized minimum trapping distance are derived. We employ a variant of the Gallager-Zyablov-Pinsker bit flipping decoding algorithm on a binary symmetric channel, where the analysis is based on the factor graph of the code. In particular, we show that the minimum trapping distance can be determined by solving a non-linear optimization problem. As a result we find that the minimum trapping distance grows linearly with block length for code rates of 1/3 and smaller, albeit with very small growth rate coefficients.
Wireless sensor networks are becoming increasing important due to their outstanding ability to detect and transmit real-time and wide application in many fields. Reducing energy consumption and extending lifetime of n...
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ISBN:
(纸本)9787900719706
Wireless sensor networks are becoming increasing important due to their outstanding ability to detect and transmit real-time and wide application in many fields. Reducing energy consumption and extending lifetime of networks are important targets in the design of wireless sensor networks. In this paper, an optimal scheme is proposed based on mixed routing. the switch factor is presented and the optimal problem is converted into a nonlinear programming problem. The target is to optimize the lifetime of bottleneck node. The optimal solution is gained by the sub-gradient iterative algorithm. The simulations show that the lifetime of the networks is extended effectively.
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