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Portfolio adjusting optimization under credibility measures

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2010年第5期234卷 1458-1465页

作者： Zhang, Xili Zhang, Wei-Guo Cai, Ruichu S China Univ Technol Sch Business Adm Guangzhou 510641 Peoples R China S China Univ Technol Sch Engn & Comp Sci Guangzhou 510641 Peoples R China

This paper discusses portfolio adjusting problems for an existing portfolio. The returns of risky assets are regarded as fuzzy variables and a class of credibilistic mean-variance adjusting models with transaction costs are proposed on the basis of credibility theory. Under the assumption that the returns of risky assets are triangular fuzzy variables, the optimization models are converted into crisp forms. Furthermore, we employ the sequential quadratic programming method to work out the optimal strategy. Numerical examples illustrate the effectiveness of the proposed models and the influence of the transaction costs in portfolio selection. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Portfolio adjusting Possibility theory Credibility measure Transaction costs sequential quadratic programming method

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Rotor blade aerodynamic shape optimization based on high-efficient optimization method

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2020年第2期234卷 375-387页

作者： Wang, Qing Zhao, Qijun Lanzhou Univ Technol Coll Energy & Power Engn Lanzhou Gansu Peoples R China Nanjing Univ Aeronaut & Astronaut Natl Key Lab Sci & Technol Rotorcraft Aeromech Nanjing 210016 Jiangsu Peoples R China

In order to design a high-performance rotor, a high-efficient optimization method is established by coupling Kriging model and sequential quadratic programming with high-accuracy computational fluid dynamics method. In order to obtain the global optimal design point, the initial blade shape is optimized by using the Kriging model coupled with genetic algorithm based on the baseline rotor blade (Helishape 7A rotor). After that, the modified sequential quadratic programming method is employed to search the final blade shape based on the initial blade shape deeply. In the optimal process, the regions of design variables are restricted considering rotor dynamic characteristics. As a result, a new shape of rotor blade with characters of nonlinear twist, variational chord length, complex swept, and anhedral distributions is obtained. Compared with the baseline rotor, blade-tip vortex of the final optimized rotor is significantly weakened, the figure of merit of the final optimized rotor increases about 3.42%, and the peak of sound pressure decreases about 16.9%. At the same time, it is demonstrated that the final optimized rotor has better forward flight characteristics.

关键词： Helicopter rotor aerodynamic performance optimization sequential quadratic programming method N-S equations

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Energy-efficient QoS-based OCDMA networks aided by nonlinear programming methods

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2019年 98卷 144-155页

作者： Pendeza Martinez, Cristiane A. Durand, Fabio Renan Abrao, Taufik Univ Tecnol Fed Parana Campus Cornelio Procopio BR-86300000 Cornelio Procopio PR Brazil Univ Estadual Londrina Dept Elect Engn Rod Celso Garcia Cid PR445POB 10-011 BR-86057970 Londrina PR Brazil

One of the advantages of the optical code division multiple access (OCDMA) system networks over other multiple access methods is the ability to provide differentiated classes of quality of service (QoS) for different users. The performance of the OCDMA networks is mainly limited by the multi-access interference (MAI) coming from other users sharing the same spectral resources. The suitable resource allocation in OCDMA networks allows greater capacity and the reliable deployment of the available resources in the network. This work aiming at applying and analyzing four analytical optimization methods applied to energy efficiency (EE) maximization of OCDMA networks. Hence, such optimization methods were applied and their performance-complexity tradeoffs are compared, namely the augmented Lagrangian method (ALM) (Hadi and Pakravan, 2018), sequential quadratic programming method (SQP), majoration-minimization (MaMi) approach (Sun et al., 2017;Stoica, 2004), as well as Dinkelbach's method (DK). Tests were performed considering practical and realistic OCDMA networks with a wide range of nodes, typically K = {8;16: 32} nodes. The evaluated optimization methods were able to achieve convergence and perform suitably to solve the optical EE-OCDMA optimization problem. However, in a few specific high loading system configurations, the DK method did not reach full convergence;besides DK processing time was much greater compared to the promising ALM, SQP and MaMi EE-OCDMA optimization approaches. (C) 2018 Elsevier GmbH. All rights reserved.

关键词： Energy efficiency OCDMA networks Augmented Lagrangian method sequential quadratic programming method Majoration-minimization Dinkelbach's fractional optimization method CvX

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An equivalent nonlinear optimization model with triangular low-rank factorization for semidefinite programs

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OPTIMIZATION methodS & SOFTWARE 2023年第6期38卷 1296-1310页

作者： Yamakawa, Yuya Ikegami, Tetsuya Fukuda, Ellen H. H. Yamashita, Nobuo Kyoto Univ Grad Sch Informat Yoshida HonmachiSakyo Ku Kyoto 6068501 Japan Yahoo Japan Corp Data & Sci Solut Grp Technol Grp Chiyoda Ku Tokyo Japan

In this paper, we propose a new nonlinear optimization model to solve semidefinite optimization problems (SDPs), providing some properties related to local optimal solutions. The proposed model is based on another nonlinear optimization model given by [S. Burer and R. Monteiro, A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization, Math. Program. Ser. B 95 (2003), pp. 329-357], but it has several nice properties not seen in the existing one. Firstly, the decision variable of the proposed model is a triangular low-rank matrix. Secondly, the existence of a strict local optimum of the proposed model is guaranteed under some conditions, whereas the existing model has no strict local optimum. In other words, it is difficult to construct solution methods equipped with fast convergence using the existing model. We also present some numerical results, showing that the use of the proposed model allows to deliver highly accurate solutions.

关键词： Semidefinite optimization problems nonlinear optimization problems sequential quadratic programming method triangular low-rank factorization

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A global-local hybrid strategy with adaptive space reduction search method for structural health monitoring

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APPLIED MATHEMATICAL MODELLING 2023年第1期121卷 231-251页

作者： Zhang, Guangcai Wan, Chunfeng Xue, Songtao Xie, Liyu Southeast Univ Key Lab Concrete & Prestressed Concrete Struct Minist Educ Nanjing Peoples R China Tongji Univ Res Inst Struct Engn & Disaster Reduct Coll Civil Engn Shanghai Peoples R China Tohoku Inst Technol Dept Architecture Sendai Japan

The difficulty in computational convergence poses challenges of application for traditional heuristic optimization algorithms to solve the optimization-based structural identification problem, especially for the large-scale and complex structural systems where considerable number of unknown parameters and degrees of freedom involved. Unlike the classic identification methods, in this paper, a novel hybrid strategy, coarsely exploring the relatively large search limits with the improved Jaya algorithm and adaptive search space reduction method in the global stage, and then fine-tuning the identified best solution with local optimization methods to the optimum in the local stage, is proposed and evaluated. The improved Jaya algorithm includes three improvements compared to its original version, fuzzy clustering competitive learning, experience learning and Cauchy mutation mechanisms. Gradient based Levenberg-Marquardt method, sequential quadratic programming method and non-gradient based Nelder-Mead simplex method are inserted as local mathematical optimizers to further enhance identification accuracy and efficiency. The superiority of proposed improved Jaya algorithm is validated in optimizing classical and CEC05 benchmark functions by comparing with several state-of-the-art algorithms. Furthermore, the effectiveness of proposed global-local hybrid method is verified by a numerical example of truss structure and an experimental test of the steel grid benchmark structure with incomplete set of noise-polluted measurements. The statistical results show that the improved Jaya algorithm and adaptive search space reduction method combined with sequential quadratic programming can achieve better performance in structural damage identification than other methods.

关键词： Structural identification Hybrid method Jaya algorithm Levenberg-marquardt method sequential quadratic programming method Nelder-mead simplex method

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Global and local convergence of a nonmonotone SQP method for constrained nonlinear optimization

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2014年第3期59卷 435-473页

作者： Shen, Chungen Zhang, Lei-Hong Wang, Bo Shao, Wenqiong Shanghai Finance Univ Dept Appl Math Shanghai 201209 Peoples R China Shanghai Univ Finance & Econ Dept Appl Math Shanghai 200433 Peoples R China Nanjing Univ Finance & Econ Sch Appl Math Shanghai 200092 Peoples R China Wayne State Univ Ind & Syst Engn Dept Detroit MI 48202 USA

In this paper, we propose a robust sequential quadratic programming (SQP) method for nonlinear programming without using any explicit penalty function and filter. The method embeds the modified QP subproblem proposed by Burke and Han (Math Program 43:277-303, 1989) for the search direction, which overcomes the common difficulty in the traditional SQP methods, namely the inconsistency of the quadratic programming subproblems. A non-monotonic technique is employed further in a framework in which the trial point is accepted whenever there is a sufficient relaxed reduction of the objective function or the constraint violation function. A forcing sequence possibly tending to zero is introduced to control the constraint violation dynamically, which is able to prevent the constraint violation from over-relaxing and plays a crucial role in global convergence and the local fast convergence as well. We prove that the method converges globally without the Mangasarian-Fromovitz constraint qualification (MFCQ). In particular, we show that any feasible limit point that satisfies the relaxed constant positive linear dependence constraint qualification is also a Karush-Kuhn-Tucker point. Under the strict MFCQ and the second order sufficient condition, furthermore, we establish the superlinear convergence. Preliminary numerical results show the efficiency of our method.

关键词： sequential quadratic programming method Non-monotonicity Convergence analysis RCPLD Strict MFCQ

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Thrust allocation logic of dynamically positioned offshore vessel

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SHIPS AND OFFSHORE STRUCTURES 2010年第3期5卷 243-251页

作者： Jeyasenthil, Ramamoorthy Dasgupta, Jyotisman Larsen & Toubro Ltd Engn & Construct Div FSBU Bombay 400072 Maharashtra India

In dynamic positioning (DP) systems, 'thrust allocation' is the problem of determining the thrust and direction of each of the 'n' thrusters in an over-actuated offshore vessel from the desired forces and moment derived in the control law. This is formulated as a non-linear optimisation problem, where the objective is to minimise the use of control effort subject to the constraints, such as actuator rate and power constraints as well as other operational constraints. This paper presents the thrust allocation method for vessels equipped with azimuth thrusters, where the non-linear constrained allocation problem has been solved by the sequential quadratic programming (SQP) method. Simulation results are presented for a semi-submersible, where constraint compliance has been satisfactorily achieved.

关键词： thrust allocation azimuth thrusters dynamic positioning sequential quadratic programming method non-linear constrained optimisation

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Optimal control of the power ramp rate with flicker mitigation for directly grid connected wind turbines

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2020年第2期96卷 141-150页

作者： Jalalabadi, Esmaeil Salehizadeh, Mohammad Reza Kian, Ashkan Rahimi Univ Tehran Coll Engn Sch ECE SNLCIPCE Kargar St Tehran *** Iran Islamic Azad Univ Dept Elect Engn Marvdasht Branch Tehran Iran

In this paper, a detailed mathematical optimization model of electrolyzer/fuel cell technology connected to the grid through limited rating converters is developed. The model is so defined that it can tackle voltage fluctuation and meet the power ramp rate limitations inflicted by integration of constant-speed wind turbines at the Point of Common Coupling. The flicker mitigation and power ramp rate control problem in the presence of wind generation and variable electrical loads is defined as a nonlinear constrained optimization problem, in which voltage fluctuation is minimized as the objective function and the power ramp rate limitations are respected by the defined real-time ramp rate constraint. The problem is solved using the sequential quadratic programming method, which is a fast solver, by adjusting suitable initial points to be appropriate for real-time applications. The simulation results validate the efficiency of the proposed method and show dramatic improvement in flicker mitigation, power ramp rate control, and system rating reduction in comparison with the proportional-integral control method that was developed in previous studies.

关键词： Constant-speed wind turbine power ramp rate flicker mitigation optimal real-time control sequential quadratic programming method

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Selection of appropriate approximation schemes in multi-disciplinary engineering optimization

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ADVANCES IN ENGINEERING SOFTWARE 2000年第6期31卷 385-389页

作者： Fluery, C Zhang, WH Univ Liege LTAS Aerosp Lab B-4000 Liege Belgium

Convex approximation methods used in structural optimization are discussed in this paper. These methods ranging from CONvex LINearization method (CONLIN), the method of Moving Asymptotes (MMA) to the sequential quadratic programming method (SQP) can be basically classified as monotonic and non-monotonic approximations. It is shown that for the considered problems of different nature, the achievement of a successful and efficient design will essentially depend upon whether approximation schemes can be appropriately selected. To ensure the approximation quality, a Generalized method of the Moving Asymptotes (GMMA) and a Diagonal quadratic Approximation (DQA) based optimizers are developed, respectively, in this work. In addition, it can be seen that the mixed approximation DQA-GMMA can be also established. Numerical examples of truss design will be used to illustrate these methods. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

关键词： method of moving asymptotes sequential quadratic programming method convex approximation methods

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A study on the optimization method for a multi-body system using the response surface analysis

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2009年第4期23卷 950-953页

作者： Jung, Sung-Pil Park, Tae-Won Jun, Kab-Jin Yoon, Ji-Won Lee, Soo-Ho Chung, Won-Sun Ajou Univ Dept Mech Engn Suwon 443749 South Korea Ajou Univ Grad Sch Mech Engn Suwon 443749 South Korea Korea Automot Technol Inst Body Chassis Reliabil Div Cheonan 330912 South Korea

An optimization method, which minimizes the characteristic value of a system using response surface analysis, is presented. Plackett-Burman design is used as a screening method. Using the response surface analysis, second order recursive model function is estimated as an objective function. To verify the reliability of the model function, an F-test based on the analysis of variances table is used. Lastly, the sequential quadratic-programming method is used to find the value of design parameters. By applying the preceding procedure to a multi-body dynamic model, the optimization process presented in this study is verified.

关键词： Design of experiments Plackett-Burman design Central composite design Analysis of variance sequential quadratic programming method

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