Teaching Documents by hoai an
Papers by hoai an
Mẫu giường ngủ gỗ công nghiệp đẹp nhất hiện nay
Journal of Convex Analysis, Nov 27, 1995
CiteSeerX - Document Details (Isaac Councill, Lee Giles): this paper the stability of the Lagrang... more CiteSeerX - Document Details (Isaac Councill, Lee Giles): this paper the stability of the Lagrangian duality in nonconvex quadratic minimization over Euclidean balls and spheres. As direct consequences we state both global optimality conditions in these problems and detailed ...
Proceedings of the 7th ACM international symposium on Mobility management and wireless access - MobiWAC '09, 2009
This paper introduces Blackbone2, a novel fully decentralized algorithm that aims at creating a r... more This paper introduces Blackbone2, a novel fully decentralized algorithm that aims at creating a robust backbone in ad hoc networks. Backbone robustness is supported by a 2-Connected m-dominating Set, 2, m-CDS, and decentralization relies on the usage of two rules that only require two-hop knowledge in order to reduce the use of bandwidth. Blackbone2 deterministic approach guarantees a density-independent valid solution and is proved correct. The algorithm is also characterized by its efficient theoretical computation time, O(∆ 2 ) with ∆ the average number of neighbors, which outperforms known solutions. The domination parameter, m, can be increased without changing the theoretical computation time. Efficiency of the Blackbone2 algorithm compared to the equivalent literature solutions is illustrated through simulations of a large panel of networks with a wide density range.
Lecture Notes in Computer Science, 2009
In this paper, we propose a new approach based on DC (Difference of Convex functions) programming... more In this paper, we propose a new approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) to perform clustering via minimum sum-of-squares Euclidean distance. The so called Minimum Sum-of-Squares Clustering (MSSC in short) is first formulated in the form of a hard combinatorial optimization problem. It is afterwards recast as a (continuous) DC program with the
2010 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010
AbstractIn this article, we present a new continuous approach based on DC (Difference of Convex ... more AbstractIn this article, we present a new continuous approach based on DC (Difference of Convex functions) programming and DC algorithms (DCA) to the Discrete Tomography. We are concerned with the reconstruction of binary images from their projections in a smaller ...
2010 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010
In this paper, we consider the task allocation models, in which we seek to assign a set of m unma... more In this paper, we consider the task allocation models, in which we seek to assign a set of m unmanned aerial vehicles (UAVs) to a set of n tasks in an optimal way. The optimality is quantified using target scores. This problem is NP-hard. To solve it, we propose an approach based on the Cross-Entropy (CE) method. The computational experiments
Lecture Notes in Computer Science, 2011
Inventory routing problem (IRP) has received growing attention from both researchers and supply c... more Inventory routing problem (IRP) has received growing attention from both researchers and supply chain planners. It can be formulated as a mixed 0-1 nonlinear programming problem that is difficult to solve. We propose a new approach based on DC (Difference of Convex Functions) programming and DCA (DC Algorithm) for solving this challenging problem. Using an exact penalty technique and a decomposition technique, the original problem is transformed into an equivalent DC problem. DCA applied on the resulting problem gives the promising results.
Lecture Notes in Computer Science, 2010
This paper presents a new robust approach to the task assignment of unmanned aerial vehicles (UAV... more This paper presents a new robust approach to the task assignment of unmanned aerial vehicles (UAVs) operating in uncertain environments whose the objective is maximizing the target score. The intrinsic uncertainty imbedded in military operations makes the problem more challenging. Scalability and robustness are recognized as two main issues. We deal with these issues by an approach based on DC
Modeling, Simulation and Optimization of Complex Processes, 2008
We propose in this work a deterministic continuous approach for constructing highly nonlinear bal... more We propose in this work a deterministic continuous approach for constructing highly nonlinear balanced Boolean functions, which is an interesting and open question in Cryptography. Our approach is based on DC (Difference of Convex functions) programming and DCA (DC optimization Algorithms). We first formulate the problem in the form of a combinatorial optimization problem, more precisely a mixed 0-1 linear program. By using exact penalty technique in DC programming, this problem is reformulated as polyhedral DC program. We next investigate DC programming and DCA for solving this latter problem. Preliminary numerical results show that the proposed algorithm is promising and more efficient than some heuristic algorithms presented in .
2009 International Multiconference on Computer Science and Information Technology, 2009
Time-index formulation for the earliness tardiness scheduling problem has received a great attent... more Time-index formulation for the earliness tardiness scheduling problem has received a great attention from many researchers because lower bound obtained by linear relaxation is rather good. Much work is devoted to tackle its upper bound. In this paper, we consider this formulation by additionally proposing a deadline for each job. We also propose an approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) to find upper bound efficiently for this problem. The results obtained are promising.
2008 IEEE International Conference on Research, Innovation and Vision for the Future in Computing and Communication Technologies, 2008
In this paper we introduce a new method using the zero-norm l0 for the combined feature selection... more In this paper we introduce a new method using the zero-norm l0 for the combined feature selection-supervised classification problem. Discontinuity at the origin for l0 makes the solution of the corresponding optimization problem difficult. To overcome this drawback we use a robust DC (difference of convex functions) programming approach which is a general framework for non-convex continuous optimisation. We consider
2011 IEEE International Ultrasonics Symposium, 2011
Simulation of ultrasound (US) images based on computed tomography (CT) data has previously been p... more Simulation of ultrasound (US) images based on computed tomography (CT) data has previously been performed with different approaches. Shadowing effects are normally pronounced in US images, so they should be included in the simulation. In this study, a new method to introduce shadowing effects has been developed which makes the simulated US images appear more realistic. US images of a cod (Gadus morhua) were obtained with a BK Medical 2202 ProFocus US scanner with a dedicated research interface giving access to beamformed RF data. The center frequency of the transmit pulse was 10 MHz. In transmit mode, the focus point was at 45 mm. 384 US focused beams were emitted to create the image. CT images with a slice thickness of 0.5 mm, and a pixel size of 0.2 x 0.2 mm, were obtained with an Aquilion ONE Toshiba CT scanner. CT data were mapped from Hounsfield Units (HU) to backscatter (BST), attenuation (ATT) coefficients, and characteristic acoustic impedance (CAI) with a new mapping method. The new approach uses focused beam tracing to create maps of the transmission coefficient (TRC) and then the scattering strength map (SSM). There were 384 maps of SSM corresponding to 384 emissions. Finally an average SSM map was calculated. Field II was used to simulate an US image with dimensions of 38.9 mm x 55.3 mm x 4.5 mm, using 10 6 point scatterers. Since no quantitative method to assess quality of a simulated US image compared to a measured one exists, visual inspection was used. The method gives diffuse shadows that are similar to the ones observed in measurements on real objects.
SIAM Journal on Optimization, 1998
Abstract. This paper is devoted to difference of convex functions (dc) optimization: dc duality, ... more Abstract. This paper is devoted to difference of convex functions (dc) optimization: dc duality, local and global optimality conditions in dc programming, the dc algorithm (DCA), and its application to solving the trust-region problem. The DCA is an iterative method that is quite different ...
Pattern Recognition, 2014
The purpose of this paper is to develop new efficient approaches based on DC (Difference of Conve... more The purpose of this paper is to develop new efficient approaches based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) to perform clustering via minimum sum-of-squares Euclidean distance. We consider the two most widely used models for the so-called Minimum Sum-of-Squares Clustering (MSSC in short) that are a bilevel programming problem and a mixed integer program. Firstly, the mixed integer formulation of MSSC is carefully studied and is reformulated as a continuous optimization problem via a new result on exact penalty technique in DC programming. DCA is then investigated to the resulting problem. Secondly, we introduce a Gaussian kernel version of the bilevel programming formulation of MSSC, named GKMSSC. The GKMSSC problem is formulated as a DC program for which a simple and efficient DCA scheme is developed. A regularization technique is investigated for exploiting the nice effect of DC decomposition and a simple procedure for finding good starting points of DCA is developed. The proposed DCA schemes are original and very inexpensive because they amount to computing, at each iteration, the projection of points onto a simplex and/or onto a ball, and/or onto a box, which are all determined in the explicit form. Numerical results on real word datasets show the efficiency, the scalability of DCA and its great superiority with respect to k-means and kernel k-means, standard methods for clustering.
Optimization, 2001
... LE THI HOAI AN and PHAM DINH TAO+ ... among them branch-and-bound algorithms whose branch-ing... more ... LE THI HOAI AN and PHAM DINH TAO+ ... among them branch-and-bound algorithms whose branch-ing operation takes place only in the "negative eigenvalues space" have been shown to be efficient (see eg, Benson [5], Kalantari-Rosen [15], Philips-Rosen [26], Phong-An-Tao ...
Optimization, 2010
Both the efficient and weakly efficient sets of an affine fractional vector optimization problem,... more Both the efficient and weakly efficient sets of an affine fractional vector optimization problem, in general, are neither convex nor given explicitly. Optimization problems over one of these sets are thus nonconvex. We propose two methods for optimizing a real-valued function over the efficient and weakly efficient sets of an affine fractional vector optimization problem. The first method is a
Operations Research Letters, 1995
A decomposition branch and bound approach is considered for the global minimization of an indefin... more A decomposition branch and bound approach is considered for the global minimization of an indefinite quadratic function over a polytope. The objective function is a sum of a nonseparable convex part and a separable concave part. In many large-scale problems the number of ...
Mathematical Programming, 2000
In this paper we investigate two approaches to minimizing a quadratic form subject to the interse... more In this paper we investigate two approaches to minimizing a quadratic form subject to the intersection of finitely many ellipsoids. The first approach is the d.c. (difference of convex functions) optimization algorithm (abbr. DCA) whose main tools are the proximal point algorithm and/or the projection subgradient method in convex minimization. The second is a branch-and-bound scheme using Lagrangian duality for bounding and ellipsoidal bisection in branching. The DCA was first introduced by Pham Dinh in 1986 for a general d.c. program and later developed by our various work is a local method but, from a good starting point, it provides often a global solution. This motivates us to combine the DCA and our branch and bound algorithm in order to obtain a good initial point for the DCA and to prove the globality of the DCA. In both approaches we attempt to use the ellipsoidal constrained quadratic programs as the main subproblems. The idea is based upon the fact that these programs can be efficiently solved by some available (polynomial and nonpolynomial time) algorithms, among them the DCA with restarting procedure recently proposed by Pham Dinh and Le Thi has been shown to be the most robust and fast for large-scale problems. Several numerical experiments with dimension up to 200 are given which show the effectiveness and the robustness of the DCA and the combined DCA-branch-and-bound algorithm.
Uploads
Teaching Documents by hoai an
Papers by hoai an