检索结果-内蒙古大学图书馆

Smoothing approach of lower order exact penalty function for nonlinear constrained optimization problems

OPTIMIZATION AND ENGINEERING 2025年 1-27页

作者： Ren, Yufei Shang, Youlin Zhang, Zhixian Jia, Zihao Henan Univ Sci & Technol Sch Math & Stat Luoyang 471023 Henan Peoples R China

In this paper, we propose two new smoothing approximation to the lower order exact penalty functions for nonlinear optimization problems with inequality constraints. Firstly, the error estimation between smoothed penalty function, non-smooth penalty function and original function is investigated. By using these new smooth penalty functions, nonlinear optimization problems with inequality constraints are transformed into unconstrained optimization problems. Then, based on each smoothed penalty function, we propose an algorithm to find the approximate optimal solution of the original constrained optimization problem, and prove the convergence of the proposed algorithm. The effectiveness of the smoothed penalty function is demonstrated through numerical examples, indicating that the algorithm is effective.

关键词： constrained nonlinear programming Lower order exact penalty function Smoothing method Second order sufficient condition

来源：评论

学校读者我要写书评

暂无评论

Data Discernment for Affordable Training in Medical Image Segmentation

引用

IEEE TRANSACTIONS ON MEDICAL IMAGING 2023年第5期42卷 1431-1445页

作者： Song, Youyi Yu, Lequan Lei, Baiying Choi, Kup-Sze Qin, Jing Hong Kong Polytech Univ Ctr Smart Hlth Sch Nursing Hung Hom Hong Kong Peoples R China Univ Hong Kong Dept Stat & Actuarial Sci Pok Fu Lam Hong Kong Peoples R China Shenzhen Univ Sch Biomed Engn Shenzhen 518060 Peoples R China

Collecting sufficient high-quality training data for deep neural networks is often expensive or even unaffordable in medical image segmentation tasks. We thus propose to train the network by using external data that can be collected in a cheaper way, e.g., crowd-sourcing. We show that by data discernment, the network is able to mine valuable knowledge from external data, even though the data distribution is very different from that of the original (internal) data. We discern the external data by learning an importance weight for each of them, with the goal to enhance the contribution of informative external data to network updating, while suppressing the data that are 'useless' or even 'harmful'. An iterative algorithm that alternatively estimates the importance weight and updates the network is developed by formulating the data discernment as a constrained nonlinear programming problem. It estimates the importance weight according to the distribution discrepancy between the external data and the internal dataset, and imposes a constraint to drive the network to learn more effectively, compared with the network without using the external data. We evaluate the proposed algorithm on two tasks: abdominal CT image and cervical smear image segmentation, using totally 6 publicly available datasets. The effectiveness of the algorithm is demonstrated by extensive experiments. Source codes are available at: https://***/YouyiSong/Data-Discernment.

关键词： Training Image segmentation Biomedical imaging Task analysis Training data programming Annotations Data discernment affordable training constrained nonlinear programming medical image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Resource Allocation Method in Multi-access Edge Computing Environment Based on Deep Reinforcement Learning 17

A Resource Allocation Method in Multi-access Edge Computing ...

引用

17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Li, Huilin Nakamura, Hiroshi Takase, Hideki The University of Tokyo Tokyo Japan

ISBN: (纸本)9798331530471

In order to help user terminal devices (UTDs) efficiently handle computation-intensive and delay-sensitive tasks, the use of multi-access edge computing (MEC) has been proposed. However, owing to the performance limitations of UTDs and limited network resources, optimizing the energy consumption of UTDs under the constraint of a certain delay condition remains a key area of research. Therefore, this paper presents a resource allocation optimization strategy for MEC environments. First, we formulated the optimization problem as a constrained nonlinear programming problem, with the aim of minimizing the total time delay and energy consumption of UTDs under a specific delay constraint. Second, we proposed a reinforcement learning algorithm that uses an actor network to predict the next action based on the current state and a critic network to evaluate the quality of the prediction. A stable convergence solution for the original optimization problem was obtained within a limited number of training episodes. Finally, the performance of the proposed algorithm was compared with that of other classical methods, which demonstrated that the proposed algorithm outperforms other methods. © 2024 IEEE.

关键词： constrained nonlinear programming deep reinforcement learning multi-access edge computing resource allocation

来源：评论

学校读者我要写书评

暂无评论

Form-finding of tensegrity structures via rank minimization of force density matrix

引用

ENGINEERING STRUCTURES 2021年 227卷 111419-111419页

作者： Wang, Yafeng Xu, Xian Luo, Yaozhi Zhejiang Univ Coll Civil Engn Architecture 866 Yuhangtang Rd Hangzhou 310058 Zhejiang Peoples R China Swiss Fed Inst Technol EPFL Sch Architecture Civil & Environm Engn ENAC Appl Comp & Mech Lab IMAC CH-1015 Lausanne Switzerland

This study proposes a general computational framework for the form-finding of tensegrity structures. The procedure is divided into two stages in which the member force densities and nodal coordinates are obtained respectively. In the first stage, the determination of force densities is transformed into a rank minimization problem regarding the force density matrix and then formulated into a semi-definite programming. The unilaterality condition of member forces and the positive semi-definiteness condition of force density matrix are incorporated as constraints. In the second stage, the determination of nodal coordinates is formulated into a constrained nonlinear programming model. The nodal positions and member lengths are assigned as constraints and auxiliary variables are introduced to homogenize the member lengths. The proposed formulation bypasses the number of self-stress states in a tensegrity structure thus applies to both tensegrity structures with single and multiple self-stress states. Different from existing studies that are based on the minimum required rank deficiency condition of force density matrix, the proposed method can handle tensegrity structures that have a force density matrix with rank deficiency greater than the required minimum number. Several examples are presented to verify the effectiveness of the proposed method on different types of tensegrity structures.

关键词： Tensegrity structure Form-finding Force density method Rank minimization Semi-definite programming constrained nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

Saddle point and exact penalty representation for generalized proximal Lagrangians

引用

JOURNAL OF GLOBAL OPTIMIZATION 2012年第4期54卷 669-687页

作者： Zhou, Jinchuan Xiu, Naihua Wang, Changyu Shandong Univ Technol Dept Math Sch Sci Zibo 255049 Peoples R China Beijing Jiaotong Univ Dept Math Sch Sci Beijing 100044 Peoples R China Qufu Normal Univ Inst Operat Res Qufu 273165 Peoples R China

In this paper, we introduce a generalized proximal Lagrangian function for the constrained nonlinear programming problem and discuss existence of its saddle points. In particular, the local saddle point is obtained by using the second-order sufficient conditions, and the global saddle point is given without requiring compactness of constraint set and uniqueness of the optimal solution. Finally, we establish equivalent relationship between global saddle points and exact penalty representations.

关键词： constrained nonlinear programming Generalized proximal Lagrangian Saddle points Exact penalty representations

来源：评论

学校读者我要写书评

暂无评论

An exact penalty-Lagrangian approach for large-scale nonlinear programming

引用

OPTIMIZATION 2011年第1-2期60卷 223-252页

作者： Di Pillo, G. Liuzzi, G. Lucidi, S. CNR Ist Anal Sistemi & Informat A Ruberti I-00185 Rome Italy Univ Roma La Sapienza Dipartimento Informat & Sistemist A Ruberti I-00185 Rome Italy

nonlinear programming problems with equality constraints and bound constraints on the variables are considered. The presence of bound constraints in the definition of the problem is exploited as much as possible. To this aim, an efficient search direction is defined which is able to produce a locally and superlinearly convergent algorithm and that can be computed in an efficient way by using a truncated scheme suitable for large scale problems. Then, an exact merit function is considered whose analytical expression again exploits the particular structure of the problem by using an exact augmented Lagrangian approach for equality constraints and an exact penalty approach for the bound constraints. It is proved that the search direction and the merit function have some strong connections which can be the basis to define a globally convergent algorithm with superlinear convergence rate for the solution of the constrained problem.

关键词： constrained nonlinear programming exact penalty-Lagrangian method

来源：评论

学校读者我要写书评

暂无评论

GLOBAL COMPETITIVE RANKING FOR CONSTRAINTS HANDLING WITH MODIFIED DIFFERENTIAL EVOLUTION

GLOBAL COMPETITIVE RANKING FOR CONSTRAINTS HANDLING WITH MOD...

引用

International Conference on Evolutionary Computation Theory and Applications (ECTA 2011) / International Conference on Fuzzy Computation Theory and Applications (FCTA 2011)

作者： Azad, Abul Kalam Fernandes, Edite M. G. P. Univ Minho Sch Engn Algoritmi R&D Ctr P-4710057 Braga Portugal

ISBN: (纸本)9789898425836

constrained nonlinear programming problems involving a nonlinear objective function with inequality and/or equality constraints introduce the possibility of multiple local optima. The task of global optimization is to find a solution where the objective function obtains its most extreme value while satisfying the constraints. Depending on the nature of the involved functions many solution methods have been proposed. Most of the existing population-based stochastic methods try to make the solution feasible by using a penalty function method. However, to find the appropriate penalty parameter is not an easy task. Population-based differential evolution is shown to be very efficient to solve global optimization problems with simple bounds. To handle the constraints effectively, in this paper, we propose a modified constrained differential evolution that uses self-adaptive control parameters, a mixed modified mutation, the inversion operation, a modified selection and the elitism in order to progress efficiently towards a global solution. In the modified selection, we propose a fitness function based on the global competitive ranking technique for handling the constraints. We test 13 benchmark problems. We also compare the results with the results found in literature. It is shown that our method is rather effective when solving constrained problems.

关键词： constrained nonlinear programming Constraints handling Ranking Differential evolution

来源：评论

学校读者我要写书评

暂无评论

An Interior-Point Algorithm for nonlinear Minimax Problems

引用

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2010年第2期144卷 291-318页

作者： Obasanjo, E. Tzallas-Regas, G. Rustem, B. Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England Barclays Capital Equ Derivat Grp Systemat Trading London England

We present a primal-dual interior-point method for constrained nonlinear, discrete minimax problems where the objective functions and constraints are not necessarily convex. The algorithm uses two merit functions to ensure progress toward the points satisfying the first-order optimality conditions of the original problem. Convergence properties are described and numerical results provided.

关键词： Discrete min-max constrained nonlinear programming Primal-dual interior-point methods Stepsize strategies

来源：评论

学校读者我要写书评

暂无评论

TESTING THE EFFECTS OF ORAL INTER VENTIONS ON THE COVARIANCE OF EXCHANGE RATES IN A STATE-OF-THE-ART COMPUTATIONAL ENVIRONMENT

TESTING THE EFFECTS OF ORAL INTER VENTIONS ON THE COVARIANCE...

引用

作者： Tolga CASKURLU BILKENT UNIVERSITY

学位级别：硕士

In the last decade, both Federal Reserve System (FED) and European Central Bank (ECB) abandoned direct market interventions and relied on communica- tion as their main policy tool to affect exchange rates. This paper investigates the impacts of officials' statements (oral intervention) on the covariance of the EUR/USD and JPY/USD. Using generalized autoregressive conditional het- eroscedasticity (GARCH) model's diagonal vector error correction (DVEC) representation, we find that strengthening oral interventions in US and Japan decrease while in Eurozone increase the covariance between EUR/USD and JPY/USD. Also reversely, weakening oral interventions in US and Japan in- crease while in Eurozone decrease the covariance. Since oral interventions are explanatory variables of the conditional covariance structure of G3 currencies (USD, EUR and JPY), ignoring oral interventions may cause errors in foreign exchange (forex) covariance forecasts. During the estimation procedure, we use a different approach than the commonly practiced in the literature. We solve the resulting optimization problem from maximum likelihood estimation (MLE) of DVEC model in two steps: first by genetic algorithm (GA) and then by sequential quadratic programming (SQP) algorithm. Furthermore, to land at a better local optimal, the experiments are conducted in NEOS Servers 1. Comparing our results with those of benchmark S+ GARCH module (a com- mercial software), we find that our approach yields much higher objective value than the benchmark does. Hence, we conclude that our computational methodology provides substantial improvement to in-sample forex covariance forecasting. Our results have applications in portfolio management as well.

关键词： Central Bank Interventions constrained nonlinear programming Multivariate GARCH Conditional Correlations

来源：评论

学校读者我要写书评

暂无评论

Optimization and coordination of wide-area damping controls for enhancing the transfer capability of interconnected power systems

引用

ELECTRIC POWER SYSTEMS RESEARCH 2008年第6期78卷 1099-1108页

作者： Xie, Xiaorong Lu, Chao Tsinghua Univ Dept Elect Engn State Key Lab Secur Control & Simulat Power Syst Beijing 100084 Peoples R China

This paper proposes systematic procedures to design wide-area damping controls (WADCs) in large interconnected power systems. An efficient model reduction method is first introduced, based on the pseudo-random binary signal (PRBS) probing technique and the prediction error identification algorithm (PEM). Then, the comprehensive controllability concept, as well as its calculating method, is proposed for properly locating the supplementary damping controllers. Further, an improved modal performance index is adopted as the measure of the stabilizing effect. With various constraints taken into account to meet practical engineering requirements, finally, the optimized and coordinated tuning of WADC parameters under various operation scenarios is achieved by a constrained nonlinear programming algorithm. The proposed approach has been tested on a practical 437-machine, 2791-node interconnected power system and the simulation results have demonstrated its high effectiveness in damping inter-area oscillations and enhancing across-region transfer capabilities. (c) 2007 Elsevier B.V. All rights reserved.

关键词： constrained nonlinear programming inter-area oscillations robustness WAMS wide-area damping control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：