检索结果-内蒙古大学图书馆

A variant of the united multi-operator evolutionary algorithms using sequential quadratic programming and improved SHADE-cnEpSin

引用

INFORMATION SCIENCES 2023年第1期622卷 652-681页

作者： Hong, Libin Guo, Youjian Liu, Fuchang Wang, Ben Hangzhou Normal Univ 2318 Yuhangtang Rd Hangzhou 311121 Peoples R China

United multi-operator evolutionary algorithms (UMOEAs) combine multi-operator differ-ential evolution (DE), the multi-operator genetic algorithm (MOGA), and the covariance matrix adaption evolution strategy (CMA-ES). UMOEAs-II, an improved version of UMOEAs, uses three differential evolution variants as multi-operator differential evolution (MODE), and CMA-ES. In this study, we further reform UMOEAs-II using an improved SHADE-cnEpSin that employs a novel adaptive strategy of scaling factor F, a crossover rate cri;j updating mechanism which can calculate crossover rate for the ith individual with a particular jth component, an improved rank-based selective pressure based mutation strat-egy, and nonlinear population size reduction along with sequential quadratic programming method. The effectiveness of the improved rank-based selective pressure based mutation strategy, nonlinear population size reduction, and sequential quadratic programming are evident from the individual validations. The novel framework, enhanced the exploration and exploitation abilities, is named UMOEAs-III and is evaluated using the CEC2017 bench-mark functions. The experiments are tested on 10, 30, 50, and 100 dimensions. The exper-imental results demonstrate the outstanding performance of UMOEAs-III in both low and high-dimensional tests compared to the state-of-the-art DE-based variants and hybrid algorithms.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Differential evolution United multi -operator evolutionary algorithms sequential quadratic programming SHADE-cnEpSin Nonlinear population size reduction CMA-ES

来源：评论

学校读者我要写书评

暂无评论

A robust implementation of a sequential quadratic programming algorithm with successive error restoration

引用

OPTIMIZATION LETTERS 2011年第2期5卷 283-296页

作者： Schittkowski, K. Univ Bayreuth Dept Comp Sci D-95440 Bayreuth Germany

We consider sequential quadratic programming methods for solving constrained nonlinear programming problems. It is generally believed that these methods are sensitive to the accuracy by which partial derivatives are provided. One reason is that differences of gradients of the Lagrangian function are used for updating a quasi-Newton matrix, e.g., by the BFGS formula. The purpose of this paper is to show by numerical experimentation that the method can be stabilized substantially. The algorithm applies non-monotone line search and internal and external restarts in case of errors due to inaccurate derivatives while computing the search direction. Even in case of large random errors leading to partial derivatives with at most one correct digit, termination subject to an accuracy of 10(-7) can be achieved in 90% of 306 problems of a standard test suite. On the other hand, the original version with monotone line search and without restarts solves only 30% of these problems under the same test environment. In addition, we show how initial and periodic scaled restarts improve the efficiency in situations with slow convergence.

关键词： SQP sequential quadratic programming Nonlinear programming Line search Restart Numerical algorithm Noisy functions

来源：评论

学校读者我要写书评

暂无评论

Active-set sequential quadratic programming with variable probabilistic constraint evaluations for optimization problems under non-Gaussian uncertainties

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2010年第C6期224卷 1273-1285页

作者： Chan, K-Y Huang, Y-C Natl Cheng Kung Univ Dept Mech Engn Tainan 70101 Taiwan

Design optimization under random uncertainties are formulated as problems with probabilistic constraints. Calculating these constraints presents a major challenge in the optimization. While most research concentrates on uncertainties that are Gaussian, a great number of uncertainties in the environment are non-Gaussian. In this work, various reliability analyses for non-Gaussian uncertainties within a sequential quadratic programming framework are integrated. An analytical reliability contour (RC) is first constructed in the design space to indicate the minimal distance from the feasible boundary of a design at a desired reliability level. A safe zone contour is then created so as to provide a quick estimate of the RC. At each design iteration reliability analyses of different accuracies are selected based on the level needed, depending on the activity of a constraint. For problems with a large number of constraints and relatively few design variables, such as structural problems, the active set strategies significantly improve efficiency, as demonstrated in the examples.

关键词： reliability-based design optimization non-Gaussian random parameters reliability contour active set strategies sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Nonlinear model predictive control via feasibility-perturbed sequential quadratic programming

引用

COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2004年第1期28卷 87-121页

作者： Tenny, MJ Wright, SJ Rawlings, JB Univ Wisconsin Dept Chem Engn Madison WI 53706 USA Univ Wisconsin Dept Comp Sci Madison WI 53706 USA

Model predictive control requires the solution of a sequence of continuous optimization problems that are nonlinear if a nonlinear model is used for the plant. We describe briefly a trust-region feasibility-perturbed sequential quadratic programming algorithm ( developed in a companion report), then discuss its adaptation to the problems arising in nonlinear model predictive control. Computational experience with several representative sample problems is described, demonstrating the effectiveness of the proposed approach.

关键词： model predictive control nonlinear programming sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Optimal design of a rod shape ultrasonic motor using sequential quadratic programming and finite element method

引用

FINITE ELEMENTS IN ANALYSIS AND DESIGN 2012年 59卷 11-17页

作者： Zhang, Jian-Tao Zhu, Hua Zhou, Sheng-Qiang Zhao, Chun-Sheng Shanghai Univ Shanghai Key Lab Mfg Automat & Robot Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Nanjing Univ Aeronaut & Astronaut Precis Driving Lab Nanjing 210016 Peoples R China

Many design requirements need to be considered in designing an ultrasonic motor. To solve the multi-objective optimization problem, sequential quadratic programming and finite element method are applied to the design process. The finite element method is used for modal analysis and harmonic response analysis of the ultrasonic motor. The sequential quadratic programming is employed to determine the optimal design solution. To validate the effectiveness of the proposed method, it is applied to the optimization of a rod shape ultrasonic motor. Design results show that all the requirements of motor design are satisfied and the design indexes related to motor performance show significant improvements after optimization. A prototype motor with 15 mm in diameter is manufactured using the optimization results. The stator vibration characteristics and the motor performance are tested. The results show that this design method is available and effective for the design of ultrasonic motors. (C) 2012 Elsevier BY. All rights reserved.

关键词： Ultrasonic motor Optimization design sequential quadratic programming Finite element method Vibration mode

来源：评论

学校读者我要写书评

暂无评论

Solution of the 2-dimensional Bratu problem using neural network, swarm intelligence and sequential quadratic programming

引用

NEURAL COMPUTING & APPLICATIONS 2014年第7-8期25卷 1723-1739页

作者： Raja, Muhammad Asif Zahoor Ahmad, Siraj-ul-Islam Samar, Raza COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan Pakistan Inst Engn & Appl Sci Islamabad Pakistan COMSATS Inst Informat Technol Dept Phys Islamabad Pakistan Mohammad Ali Jinnah Univ Islamabad Pakistan

In this paper, stochastic techniques have been developed to solve the 2-dimensional Bratu equations with the help of feed-forward artificial neural networks, optimized with particle swarm optimization (PSO) and sequential quadratic programming (SQP) algorithms. A hybrid of the above two algorithms, referred to as the PSO-SQP method is also studied. The original 2-dimensional equations are solved by first transforming them into equivalent one-dimensional boundary value problems (BVPs). These are then modeled using neural networks. The optimization problem for training the weights of the network has been addressed using particle swarm techniques for global search, integrated with an SQP method for rapid local convergence. The methodology is evaluated by applying on three different test cases of BVPs for the Bratu equations. Monte Carlo simulations and extensive analyses are carried out to validate the accuracy, convergence and effectiveness of the schemes. A comparative study of proposed results is made with available exact solution, as well as, reported numerical results.

关键词： 2-Dimensional Bratu equations Neural networks Particle swarm optimization Nonlinear ODEs Memetic computing sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Power recovery of a variable nozzle turbocharged diesel engine at high altitude by response surface methodology and sequential quadratic programming

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2019年第4期233卷 810-823页

作者： Wang, Jun Shen, Lizhong Bi, Yuhua Liu, Shaohua Wan, Mingding Kunming Univ Sci & Technol Yunnan Prov Key Lab Internal Combust Engines 727 Jingming South Rd Kunming 650500 Yunnan Peoples R China

Based on a review of the research methods about diesel engine performance recovery at high altitude and an experimental investigation, by optimizing variable nozzle turbocharger (VNT) and fuel supply system calibration parameters a novel method is proposed to enhance the performance of a turbocharged diesel engine at high altitude. At an altitude of 1920 m, four calibration parameters deeply affecting performance of the diesel engine were selected at the rated power condition, that is, injection quantity, injection timing, injection pressure, and VNT nozzle opening. In order to reduce thermal load of the diesel engine running in the plateau environment, reasonable coded levels of Design of Experiments (DoE) factors were chosen, and an experimental design matrix was selected based on the Box-Behnken design. The interaction effects of the four calibration parameters on engine performance were investigated using the response surface methodology. Power recovery optimization was carried out by means of sequential quadratic programming under a minimum smoke limit and durability constraints. The results show that this performance optimization method can effectively recover engine performance at high altitude. Moreover, it can, to an extent, alleviate the problems such as deterioration of fuel consumption and high thermal load induced by the rise in elevation. With optimized calibration parameters, the rated power of the diesel engine at an altitude of 1920 m proved to be recovered to that at sea level, and there was an increase of brake specific fuel consumption by less than 3% compared with that in the plain area, which met the performance and durability requirements for general turbocharged internal combustion engines at altitudes lower than 2000 m.

关键词： Diesel engine variable nozzle turbocharger high altitude power recovery response surface methodology sequential quadratic programming

来源：评论

学校读者我要写书评

暂无评论

An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

引用

MATHEMATICAL programming 2023年第1-2期199卷 721-791页

作者： Na, Sen Anitescu, Mihai Kolar, Mladen Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Int Comp Sci Inst Berkeley CA 94704 USA Argonne Natl Lab Math & Comp Sci Div Lemont IL USA Univ Chicago Booth Sch Business Chicago IL 60637 USA

We consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for the objective that its evaluation, gradient, and Hessian are inaccessible, while one can compute their stochastic estimates by, for example, subsampling. We propose a stochastic algorithm based on sequential quadratic programming (SQP) that uses a differentiable exact augmented Lagrangian as the merit function. To motivate our algorithm design, we first revisit and simplify an old SQP method Lucidi (J. Optim. Theory Appl. 67(2): 227-245, 1990) developed for solving deterministic problems, which serves as the skeleton of our stochastic algorithm. Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified. Finally, we incorporate a recent stochastic line search procedure Paquette and Scheinberg (SIAM J. Optim. 30(1): 349-376 2020) into the non-adaptive stochastic SQP to adaptively select the random stepsizes, which leads to an adaptive stochastic SQP. The global "almost sure" convergence for both non-adaptive and adaptive SQP methods is established. Numerical experiments on nonlinear problems in CUTEst test set demonstrate the superiority of the adaptive algorithm.

关键词： Stochastic optimization sequential quadratic programming Augmented Lagrangian Exact penalty

来源：评论

学校读者我要写书评

暂无评论

A piecewise linear chaotic map and sequential quadratic programming based robust hybrid particle swarm optimization

引用

INFORMATION SCIENCES 2013年 218卷 85-102页

作者： Xu, Wenxing Geng, Zhiqiang Zhu, Qunxiong Gu, Xiangbai Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Sinopec Engn Beijing 100029 Peoples R China

This paper presents a novel robust hybrid particle swarm optimization (RHPSO) based on piecewise linear chaotic map (PWLCM) and sequential quadratic programming (SQP). The aim of the present research is to develop a new single-objective optimization approach which requires no adjustment of its parameters for both unconstrained and constrained optimization problems. This novel algorithm makes the best of ergodicity of PWLCM to help PSO with the global search while employing the SQP to accelerate the local search. Five unconstrained benchmarks, eighteen constrained benchmarks and three engineering optimization problems from the literature are solved by using the proposed hybrid approach. The simulation results compared with other state-of-art methods demonstrate the effectiveness and robustness of the proposed RHPSO for both unconstrained and constrained problems of different dimensions. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Particle swarm optimization sequential quadratic programming Chaotic optimization Piecewise linear chaotic map Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Feasibility refinement in sequential quadratic programming using parametric sensitivity analysis

引用

OPTIMIZATION METHODS & SOFTWARE 2017年第4期32卷 754-769页

作者： Geffken, Soeren Bueskens, Christof Univ Bremen Ctr Ind Math Bremen Germany

In this paper we present results that extend the sequential quadratic programming (SQP) algorithm with an additional feasibility refinement based on parametric sensitivity derivatives. The refinement is applicable without restriction on the problem dimensions in sparse SQP solvers. Parametric sensitivity analysis is a tool for post optimality analysis of the solution of a nonlinear optimization problem. For the refinement approach we apply this technique on the quadratic subproblems in order to improve the overall algorithm. The sensitivity derivatives required for this approach can be computed without noticeable computational effort as the system of linear equations to be solved coincides with the system already solved for the search direction computation. For similar algorithms in the context of post optimality analysis a linear rate of convergence has been proven and therefore an extrapolation method is applied to speed up the process. The presented algorithm has been integrated into the nonlinear program (NLP) solver WORHP and we perform a numerical study to evaluate different termination criteria for the proposed algorithm. Furthermore, numerical results on the CUTEst test set are shown.

关键词： nonlinear optimization parametric sensitivity analysis sequential quadratic programming

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：