A new class of generalized constrained multiobjective games is introduced and studied in locally FC-uniform spaces without convexity structure where the number of players may be finite or infinite and all payoff funct...A new class of generalized constrained multiobjective games is introduced and studied in locally FC-uniform spaces without convexity structure where the number of players may be finite or infinite and all payoff functions get their values in an infinite-dimensional space. By using a Himmelberg type fixed point theorem in locally FC-uniform spaces due to author, some existence theorems of weak Paxeto equilibria for the generalized constrained multiobjective games are established in locally FC-uniform spaces. These theorems improve, unify and generalize the corresponding results in recent literatures.展开更多
This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable dec...This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable decoding scheme. Then a multi-pass biased sampling method followed up by a multi-local search is used to generate a diverse and good quality initial population. The population then evolves through modified order-based recombination and mutation operators to perform exploration for promising solutions within the entire region. Mutation is performed only if the current population has converged or the produced offspring by recombination operator is too similar to one of his parents. Finally the algorithm performs an intensified local search on the best solution found in the evolutionary stage. Computational experiments using standard instances indicate that the proposed algorithm works well in both computational time and solution quality.展开更多
In this article, we introduce and study some new classes of multi-leader-follower generalized constrained multiobjective games in locally FC-uniform spaces where the number of leaders and followers may be finite or in...In this article, we introduce and study some new classes of multi-leader-follower generalized constrained multiobjective games in locally FC-uniform spaces where the number of leaders and followers may be finite or infinite and the objective functions of the followers obtain their values in infinite-dimensional spaces. Each leader has a constrained correspondence. By using a collective fixed point theorem in locally FC-uniform spaces due to author, some existence theorems of equilibrium points for the multi-leader-follower generalized constrained multiobjective games are established under nonconvex settings. These results generalize some corresponding results in recent literature.展开更多
By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential pr...By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it.Global and local superlinear/quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.展开更多
By utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of signals received at a number of receivers, a constrained least-square (CLS) algorithm for estimating ...By utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of signals received at a number of receivers, a constrained least-square (CLS) algorithm for estimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates could be exploited to constrain the solution. And without requiring apriori knowledge of TDOA and FDOA measurement noises, the proposed algorithm can satisfy the demand of practical applications. Additionally, on basis of con- volute and polynomial rooting operations, the Lagrange multipliers can be obtained efficiently and robustly allowing real-time imple- mentation and global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least square (WLS) approach especially for higher measurement noise level.展开更多
One class of effective methods for the optimization problem with inequality constraints are to transform the problem to a unconstrained optimization problem by constructing a smooth potential function. In this paper, ...One class of effective methods for the optimization problem with inequality constraints are to transform the problem to a unconstrained optimization problem by constructing a smooth potential function. In this paper, we modifies a dual algorithm for constrained optimization problems and establishes a corresponding improved dual algorithm; It is proved that the improved dual algorithm has the local Q-superlinear convergence; Finally, we performed numerical experimentation using the improved dual algorithm for many constrained optimization problems, the numerical results are reported to show that it is valid in practical computation.展开更多
Time-differences-of-arrival (TDOA) and gain-ratios-of- arrival (GROA) measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares (CWL...Time-differences-of-arrival (TDOA) and gain-ratios-of- arrival (GROA) measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares (CWLS) estimator is presented. Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem (SDP), which can be solved by using modern convex optimization algorithms. Moreover, this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good per- formance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.展开更多
By adding one variable to the equality- or inequality-constrained minimization problems, a new simple penalty function is proposed. It is proved to be exact in the sense that under mild assumptions, the local minimize...By adding one variable to the equality- or inequality-constrained minimization problems, a new simple penalty function is proposed. It is proved to be exact in the sense that under mild assumptions, the local minimizers of this penalty function are precisely the local minimizers of the original problem, when the penalty parameter is sufficiently large.展开更多
By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential ...By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it. Global and local superlinear/ quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.展开更多
A memetic algorithm (MA) for a multi-mode resourceconstrained project scheduling problem (MRCPSP) is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm (MA) for a multi-mode resourceconstrained project scheduling problem (MRCPSP) is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called "strategic oscillation" to make the search process have a higher probability to visit solutions around a "feasible boundary". One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
Deep learning has risen in popularity as a face recognition technology in recent years.Facenet,a deep convolutional neural network(DCNN)developed by Google,recognizes faces with 128 bytes per face.It also claims to ha...Deep learning has risen in popularity as a face recognition technology in recent years.Facenet,a deep convolutional neural network(DCNN)developed by Google,recognizes faces with 128 bytes per face.It also claims to have achieved 99.96%on the reputed Labelled Faces in the Wild(LFW)dataset.How-ever,the accuracy and validation rate of Facenet drops down eventually,there is a gradual decrease in the resolution of the images.This research paper aims at developing a new facial recognition system that can produce a higher accuracy rate and validation rate on low-resolution face images.The proposed system Extended Openface performs facial recognition by using three different features i)facial landmark ii)head pose iii)eye gaze.It extracts facial landmark detection using Scattered Gated Expert Network Constrained Local Model(SGEN-CLM).It also detects the head pose and eye gaze using Enhanced Constrained Local Neur-alfield(ECLNF).Extended openface employs a simple Support Vector Machine(SVM)for training and testing the face images.The system’s performance is assessed on low-resolution datasets like LFW,Indian Movie Face Database(IMFDB).The results demonstrated that Extended Openface has a better accuracy rate(12%)and validation rate(22%)than Facenet on low-resolution images.展开更多
基于特征提取的图像分类算法的核心问题是如何对特征进行有效编码.局部约束线性编码(Locality-constrained linear coding,LLC)因其良好的特征重构性与局部平滑稀疏性,已取得了很好的分类性能.然而,LLC编码的分类性能对编码过程中的近邻...基于特征提取的图像分类算法的核心问题是如何对特征进行有效编码.局部约束线性编码(Locality-constrained linear coding,LLC)因其良好的特征重构性与局部平滑稀疏性,已取得了很好的分类性能.然而,LLC编码的分类性能对编码过程中的近邻数k的大小比较敏感,随着k的增大,编码中的某些负值元素与正值元素的差值绝对值也可能增大,这使得LLC越来越不稳定.本文通过在LLC优化模型的目标方程中引入非负约束,提出了一种新型编码方式,称为非负局部约束线性编码(Non-negative locality-constrained linear coding,NNLLC).该模型一般采取迭代优化算法进行求解,但其计算复杂度较大.因此,本文提出两种近似非负编码算法,其编码速度与LLC一样快速.实验结果表明,在多个广泛使用的图像数据集上,相比于LLC,NNLLC编码方式不仅在分类精确率上提高了近1%~4%,而且对k的选取具有更强的鲁棒性.展开更多
基金the Natural Science Foundation of Education Department of Sichuan Province of China(No.07ZA092)the Foundation of Taiwan Science Council
文摘A new class of generalized constrained multiobjective games is introduced and studied in locally FC-uniform spaces without convexity structure where the number of players may be finite or infinite and all payoff functions get their values in an infinite-dimensional space. By using a Himmelberg type fixed point theorem in locally FC-uniform spaces due to author, some existence theorems of weak Paxeto equilibria for the generalized constrained multiobjective games are established in locally FC-uniform spaces. These theorems improve, unify and generalize the corresponding results in recent literatures.
文摘This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable decoding scheme. Then a multi-pass biased sampling method followed up by a multi-local search is used to generate a diverse and good quality initial population. The population then evolves through modified order-based recombination and mutation operators to perform exploration for promising solutions within the entire region. Mutation is performed only if the current population has converged or the produced offspring by recombination operator is too similar to one of his parents. Finally the algorithm performs an intensified local search on the best solution found in the evolutionary stage. Computational experiments using standard instances indicate that the proposed algorithm works well in both computational time and solution quality.
基金supported by the Scientific Research Fun of Sichuan Normal University(11ZDL01)the Sichuan Province Leading Academic Discipline Project(SZD0406)
文摘In this article, we introduce and study some new classes of multi-leader-follower generalized constrained multiobjective games in locally FC-uniform spaces where the number of leaders and followers may be finite or infinite and the objective functions of the followers obtain their values in infinite-dimensional spaces. Each leader has a constrained correspondence. By using a collective fixed point theorem in locally FC-uniform spaces due to author, some existence theorems of equilibrium points for the multi-leader-follower generalized constrained multiobjective games are established under nonconvex settings. These results generalize some corresponding results in recent literature.
基金Project supported by the Teaching and Research Award Program for the Outstanding YoungTeachers in Higher Education Institutes of Munistry of Education, P.R.China
文摘By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it.Global and local superlinear/quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2010AA7010422 2011AA7014061)
文摘By utilizing the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements of signals received at a number of receivers, a constrained least-square (CLS) algorithm for estimating the position and velocity of a moving source is proposed. By utilizing the Lagrange multipliers technique, the known relation between the intermediate variables and the source location coordinates could be exploited to constrain the solution. And without requiring apriori knowledge of TDOA and FDOA measurement noises, the proposed algorithm can satisfy the demand of practical applications. Additionally, on basis of con- volute and polynomial rooting operations, the Lagrange multipliers can be obtained efficiently and robustly allowing real-time imple- mentation and global convergence. Simulation results show that the proposed estimator achieves remarkably better performance than the two-step weighted least square (WLS) approach especially for higher measurement noise level.
基金Supported by the National 863 Project (2003AA002030)
文摘One class of effective methods for the optimization problem with inequality constraints are to transform the problem to a unconstrained optimization problem by constructing a smooth potential function. In this paper, we modifies a dual algorithm for constrained optimization problems and establishes a corresponding improved dual algorithm; It is proved that the improved dual algorithm has the local Q-superlinear convergence; Finally, we performed numerical experimentation using the improved dual algorithm for many constrained optimization problems, the numerical results are reported to show that it is valid in practical computation.
基金supported by the National Natural Science Foundation of China(61201282)the Science and Technology on Communication Information Security Control Laboratory Foundation(9140C130304120C13064)
文摘Time-differences-of-arrival (TDOA) and gain-ratios-of- arrival (GROA) measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares (CWLS) estimator is presented. Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem (SDP), which can be solved by using modern convex optimization algorithms. Moreover, this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good per- formance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.
基金supported by the National Natural Science Foundation of China (Nos. 10571116 and51075421)
文摘By adding one variable to the equality- or inequality-constrained minimization problems, a new simple penalty function is proposed. It is proved to be exact in the sense that under mild assumptions, the local minimizers of this penalty function are precisely the local minimizers of the original problem, when the penalty parameter is sufficiently large.
文摘By introducing a smooth merit function for the median function, a new smooth merit function for box constrained variational inequalities (BVIs) was constructed. The function is simple and has some good differential properties. A damped Newton type method was presented based on it. Global and local superlinear/ quadratic convergence results were obtained under mild conditions, and the finite termination property was also shown for the linear BVIs. Numerical results suggest that the method is efficient and promising.
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm (MA) for a multi-mode resourceconstrained project scheduling problem (MRCPSP) is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called "strategic oscillation" to make the search process have a higher probability to visit solutions around a "feasible boundary". One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
文摘Deep learning has risen in popularity as a face recognition technology in recent years.Facenet,a deep convolutional neural network(DCNN)developed by Google,recognizes faces with 128 bytes per face.It also claims to have achieved 99.96%on the reputed Labelled Faces in the Wild(LFW)dataset.How-ever,the accuracy and validation rate of Facenet drops down eventually,there is a gradual decrease in the resolution of the images.This research paper aims at developing a new facial recognition system that can produce a higher accuracy rate and validation rate on low-resolution face images.The proposed system Extended Openface performs facial recognition by using three different features i)facial landmark ii)head pose iii)eye gaze.It extracts facial landmark detection using Scattered Gated Expert Network Constrained Local Model(SGEN-CLM).It also detects the head pose and eye gaze using Enhanced Constrained Local Neur-alfield(ECLNF).Extended openface employs a simple Support Vector Machine(SVM)for training and testing the face images.The system’s performance is assessed on low-resolution datasets like LFW,Indian Movie Face Database(IMFDB).The results demonstrated that Extended Openface has a better accuracy rate(12%)and validation rate(22%)than Facenet on low-resolution images.
文摘基于特征提取的图像分类算法的核心问题是如何对特征进行有效编码.局部约束线性编码(Locality-constrained linear coding,LLC)因其良好的特征重构性与局部平滑稀疏性,已取得了很好的分类性能.然而,LLC编码的分类性能对编码过程中的近邻数k的大小比较敏感,随着k的增大,编码中的某些负值元素与正值元素的差值绝对值也可能增大,这使得LLC越来越不稳定.本文通过在LLC优化模型的目标方程中引入非负约束,提出了一种新型编码方式,称为非负局部约束线性编码(Non-negative locality-constrained linear coding,NNLLC).该模型一般采取迭代优化算法进行求解,但其计算复杂度较大.因此,本文提出两种近似非负编码算法,其编码速度与LLC一样快速.实验结果表明,在多个广泛使用的图像数据集上,相比于LLC,NNLLC编码方式不仅在分类精确率上提高了近1%~4%,而且对k的选取具有更强的鲁棒性.