Article
Computer Science, Artificial Intelligence
Filipp Skomorokhov, Jun Wang, George Ovchinnikov, Evgeny Burnaev, Ivan Oseledets
Summary: This paper focuses on multi-period portfolio selection driven by events. It proposes an event-triggering function to replicate fund managers and optimize Sharpe and Sortino ratios in the Markowitz's return-risk framework. The problem is formulated as a series of biconvex optimization problems with a variable weight and a surrogate objective function. The experiments demonstrate the effectiveness of the proposed approach in calculating market indices and equal-weighted portfolios using Sharpe and Sortino ratios.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics, Applied
Stefania Corsaro, Valentina De Simone, Zelda Marino
Summary: This paper investigates the optimal long-term investment strategy with the ability to exit the investment before maturity without severe loss. A model based on a fused lasso approach in the Markowitz context is developed to handle the problem. The split Bregman method is used to solve the non-smooth constrained optimization problem efficiently.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Business
Tianxiang Cui, Nanjiang Du, Xiaoying Yang, Shusheng Ding
Summary: This study proposes a novel DRL hyper-heuristic framework for multi-period portfolio optimization problem. Compared to traditional DRL algorithms, this approach improves performance by searching for low-level trading strategies and leverages data-driven methods and multidimensional states to obtain additional information. Experimental results demonstrate significant performance gains in real-world capital market problems.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2024)
Article
Management
Zongrun Wang, Tangtang He
Summary: This paper explores the influence of reference dependence, disappointment feelings, and risk aversion on portfolio selection, focusing on the reference point updating model. Empirical studies suggest that negative behavior often leads to the best terminal wealth in many cases.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2022)
Article
Mathematics, Applied
Daping Zhao, Lin Bai, Yong Fang, Shouyang Wang
Summary: This paper introduces a portfolio selection model that can be applied to multi-period investment and conducts numerical tests to demonstrate its superiority.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Green & Sustainable Science & Technology
Mingming Zhang, Wenwen Song, Liyun Liu, Dequn Zhou
Summary: This study explores the optimal investment strategy for power generation enterprises in China to achieve carbon neutrality. The results reveal that renewable energy generation, particularly wind power, is expected to account for more than 42% of the portfolio in all scenarios. The scenario involving the use of clean fossil fuels carries the highest level of risk, but fossil energy generation still plays a significant role in ensuring stability. The study further highlights the positive correlation between electricity price volatility and investment value and risk. Interestingly, the impact of carbon dioxide price and volatility on power generation projects is not linear.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Automation & Control Systems
Bo Li, Ranran Zhang, Yichen Sun
Summary: This paper addresses the issue of multi-period portfolio optimization under uncertain circumstances by treating the return rates of risky securities as uncertain variables and using uncertainty theory to handle experts' evaluations. A complex multi-period mean-entropy-variance model is formulated, taking into account realistic constraints such as bankruptcy, liquidity, diversification, and self-financing. The maximum return and minimum risk are achieved simultaneously in a single-objective model through normalization. Equivalent deterministic forms of secondary models for the main model are provided, and a modified root system growth algorithm is developed for better suitability. Numerical simulations confirm the effectiveness of the proposed model and algorithm.
Article
Engineering, Multidisciplinary
Zhongming Wu, Kexin Sun
Summary: A new distributionally robust mean-variance model is proposed in this study to solve the multi-period portfolio selection problem, utilizing the Wasserstein metric to capture the uncertainty of returns. The model is transformed into a tractable convex problem using duality theory, and the radius of the Wasserstein ball is estimated using a nonparametric bootstrap method. Analyzing the in-sample data indicates that the portfolio's return and risk are relatively insensitive to parameter values. A series of out-of-sample experiments demonstrate that the proposed model outperforms other models in terms of final wealth, standard deviation, and Sharpe ratio.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Computer Science, Artificial Intelligence
Ludmila Dymova, Krzysztof Kaczmarek, Pavel Sevastjanov
Summary: The study proposes a new approach to fuzzy portfolio selection based on simple criteria of portfolio risk and return, developing single-period and multi-period models successfully applied to real stock market data. The method optimizes real market decisions and incorporates stock signals into the models, enhancing the realism of the results.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Lin Jiang, Song Wang
Summary: This paper investigates a multi-period multi-objective portfolio selection problem with uncertainty, and proposes a weighted-sum approach to address the issue. Numerical examples are provided to demonstrate the effectiveness and efficiency of the proposed method.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Business, Finance
Shun Chen, Lei Ge
Summary: This research investigates a learning-based strategy for optimal investment using neural networks. By proposing an optimization problem and utilizing a neural network model, the structure can be easily implemented and final results can be obtained through deep learning software. Numerical comparison with classic solutions demonstrates the effectiveness of the learning-based strategy.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2021)
Article
Automation & Control Systems
Mirko Mazzoleni, Gabriele Maroni, Simone Formentin, Fabio Previdi
Summary: In this study, a kernel-based data-driven approach is proposed for optimizing multi-period portfolio control strategies. By minimizing the Lower Partial Moments risk measure, the method provides better trade-offs in terms of risk and investment performance while preserving convexity. Empirical results on real historical financial data demonstrate the effectiveness of the method.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Xingyu Yang, Jingui Chen, Weilong Liu, Xuejin Zhao
Summary: This paper discusses the problem of constructing the optimal multi-period portfolio for loss-averse investors in a fuzzy environment. The return rates of risky assets are considered as fuzzy numbers, and a value function based on prospect theory is used to transform the return rate into perceived value, reflecting investors' loss aversion. A new risk measure based on perceived value is proposed to account for varying risk perception levels with different degrees of loss aversion. The objectives of maximizing cumulative expected perceived value and minimizing cumulative perceived risk are formulated, and a multi-period portfolio selection model with diversification constraint is proposed. A multiple particle swarm optimization algorithm is designed to solve the model. A real case using data from the financial market is constructed to illustrate the effectiveness of the model and algorithm, showing that the proposed model can provide more reasonable strategies for investors with different degrees of loss aversion.
Article
Business
Qun Wu, Xinwang Liu, Jindong Qin, Ligang Zhou, Abbas Mardani, Muhammet Deveci
Summary: This paper aims to develop a hybrid SRI portfolio selection model using multi-criteria decision making and multi-objective optimization techniques. A case study on medical stock investment is conducted to demonstrate the robustness, effectiveness, and superiority of the proposed methodology.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Automation & Control Systems
Xing-Yu Yang, Si-Dou Chen, Wei-Long Liu, Yong Zhang
Summary: This paper addresses the multi-period portfolio problem with short selling under fuzzy environment. Three types of short selling constraints are proposed, and a multi-period possibilistic mean-semi-variance portfolio selection model with multiple short selling constraints is established. A multiple particle swarm optimization with simulated annealing is designed to solve the model. The results show that short selling has a significant impact on investment decisions, and the proposed model can help investors improve their investment return by constructing portfolio strategies with short selling.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Mathematics, Interdisciplinary Applications
Qinyun Lu, Yuanguo Zhu, Bo Li
Summary: This paper investigates the finite-time stability in mean for uncertain fractional order linear time-invariant discrete systems, introduces uncertain fractional order difference equations with nabla operators, establishes conditions for the systems driven by such equations, designs state feedback controllers, and provides examples to illustrate the effectiveness of the results.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2021)
Article
Computer Science, Artificial Intelligence
Bo Li, Yufei Sun, Kok Lay Teo
Summary: In this paper, a method for deriving an analytic optimal solution to a multi-period uncertain portfolio selection problem is proposed. The use of a new uncertain risk measure and a bi-criteria optimization model allows for the maximization of investment return while minimizing investment risk. The application of dynamic programming leads to obtaining an analytic optimal solution, which is shown to be realistic through a numerical simulation.
FUZZY OPTIMIZATION AND DECISION MAKING
(2022)
Article
Mathematics, Interdisciplinary Applications
Xin Chen, Yuanguo Zhu
Summary: This paper applies chance theory to study optimal control for uncertain random singular systems with multiple time-delays, deriving appropriate recurrence equations and discussing two kinds of optimal control problems. It provides the optimal control inputs and respective optimal values through the solvability of the obtained equations. A numerical example demonstrates the effectiveness of the theoretical results.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Multidisciplinary
Bo Li, Yadong Shu
Summary: This paper proposes the concept of skewness for uncertain random variables and presents a formula for calculating skewness. By applying this formula, the skewnesses of three special uncertain random variables are derived. Finally, the efficiency and applicability of skewness and the presented formula are demonstrated through a portfolio selection problem.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2022)
Article
Mathematics, Interdisciplinary Applications
Ziqiang Lu, Yuanguo Zhu
Summary: This paper deals with the impulsive problem for uncertain fractional dynamical system. The concept of uncertain fractional impulsive problem involving the Caputo derivative is introduced and analytic solutions to linear uncertain fractional impulsive problems are derived. Existence and uniqueness theorems are developed using the Kuratowski measure of noncompactness and fixed point theorems, respectively. An illustrative example is provided to explain the main results.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Computer Science, Artificial Intelligence
Liu He, Yuanguo Zhu, Ziqiang Lu
Summary: This paper discusses the parameter estimation problem for uncertain fractional differential equations and proposes an algorithm based on the definition of Liu process and the method of moments. The effectiveness of the algorithm is demonstrated through numerical examples and uncertain hypothesis test.
FUZZY OPTIMIZATION AND DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Xiangfa Li, Bo Li, Ting Jin, Peiyao Zheng
Summary: This paper addresses the uncertainty and randomness in financial systems, specifically focusing on the problem of uncertain random higher moments portfolio optimization. Through the proposal of a new uncertain random mean-variance-skewness-kurtosis-entropy model, along with two auxiliary models, the authors provide a comprehensive framework for portfolio optimization. Numerical simulation results confirm the practicality and validity of the proposed model, the NSGA-II algorithm, and the optimal selection criterion, with population size and parameter adjustment found to significantly impact the results, aligning with real-world observations.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Mathematics, Interdisciplinary Applications
Bo Li, Yayi Huang
Summary: Due to the complexity of security markets, there may be securities with massive effective data, invalid data, and insufficient data at the same time. This paper discusses the portfolio selection problem with different mental accounts under an uncertain random environment. It formulates an uncertain random model and presents two equivalent forms of the uncertain random portfolio model based on mental accounts. Numerical simulations are conducted to analyze the reality and practicability of the established models with two and three mental accounts.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Artificial Intelligence
Liu He, Yuanguo Zhu, Yajing Gu
Summary: In recent years, significant progress has been made on the research of parameter estimation for uncertain differential equations. However, the parameter estimation may not be directly applicable when dealing with nonparametric uncertain differential equations. In this paper, a Legendre polynomial based method is proposed for the nonparametric estimation of autonomous uncertain differential equations. Numerical examples are provided to demonstrate the acceptability of these estimations using residuals and uncertain hypothesis tests. The proposed nonparametric estimation method is applied to an atmospheric carbon dioxide model.
FUZZY OPTIMIZATION AND DECISION MAKING
(2023)
Article
Mathematics, Applied
Qinqin Xu, Yuanguo Zhu
Summary: This paper discusses the reliability of uncertain random systems, where randomness is regarded as objective indeterminacy with enough sample data, and uncertainty is referred to epistemic indeterminacy with insufficient sample data. The degradation process is modeled using an uncertain differential equation, and external shocks are driven by an uncertain random renewal process. Chance measure is applied to define the reliability index, and three types of reliability models with independent failures are presented.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Computer Science, Hardware & Architecture
Qinqin Xu, Yuanguo Zhu
Summary: This study combines system cost optimization with burn-in and preventive maintenance strategies for uncertain random systems affected by competing failure processes. The reliability optimization model proposes a chance-based reliability index, and the optimal burn-in parameters and maintenance observation time are derived using the genetic algorithm. A numerical example is provided to illustrate the application of burn-in and maintenance methods.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Computer Science, Interdisciplinary Applications
Ziqiang Lu, Yuanguo Zhu
Summary: This paper investigates the pth moment asymptotic stability of trivial solutions to uncertain dynamical systems with time-delays. The generalized expected value based on uncertainty theory is introduced and its properties are discussed. Sufficient conditions for ensuring the stability of uncertain delay systems are derived using the Lyapunov direct method. Several illustrative examples with numerical simulations are provided to demonstrate the effectiveness of the stability results.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Mathematics, Interdisciplinary Applications
Yiyu Liu, Hanjie Liu, Yuanguo Zhu
Summary: This paper investigates a numerical scheme for solving Caputo-Hadamard UFDEs arising from nonlinear uncertain dynamic systems. By defining an alpha-path and studying a formula for calculating the expected value of the UFDE, numerical algorithms for computing the inverse uncertainty distribution and the expected value of the solution are designed. Numerical examples confirm the validity and accuracy of the proposed algorithms.
FRACTAL AND FRACTIONAL
(2022)
Article
Mathematics, Applied
Yajing Gu, Yuanguo Zhu
Summary: This paper investigates a new type of optimal control problem involving a parabolic uncertain partial differential equation, where the objective function adopts an expected value criterion. The fundamental idea of Haar wavelet transformation is to approximate the proposed problem with arbitrary accuracy by converting it into an uncertain optimal control problem due to the infinitely increasing dimensions of Haar basis. The relative convergence theorem is proven, and an application to an optimal control problem with an uncertain heat equation is presented to demonstrate the effectiveness of the proposed method.
Article
Mathematics, Applied
Qinyun Lu, Yuanguo Zhu
Summary: This paper focuses on the stability of systems governed by linear fractional order uncertain difference equations, which are used to describe neural networks. The solutions to these equations are provided, and the definition of finite-time stability in measure for the proposed systems is introduced. Moreover, some sufficient conditions for checking it are achieved using fractional order difference and uncertainty theory. The relationship between finite-time stability almost surely and in measure is also discussed, and some numerical examples are analyzed to illustrate the proposed results.
MATHEMATICAL SCIENCES
(2022)
Article
Engineering, Multidisciplinary
A. A. Aganin, A. I. Davletshin
Summary: A mathematical model of interaction of weakly non-spherical gas bubbles in liquid is proposed in this paper. The model equations are more accurate and compact compared to existing analogs. Five problems are considered for validation, and the results show good agreement with experimental data and numerical solutions. The model is also used to analyze the behavior of bubbles in different clusters, providing meaningful insights.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Hao Wu, Jie Sun, Wen Peng, Lei Jin, Dianhua Zhang
Summary: This study establishes an analytical model for the coupling of temperature, deformation, and residual stress to explore the mechanism of residual stress formation in hot-rolled strip and how to control it. The accuracy of the model is verified by comparing it with a finite element model, and a method to calculate the critical exit crown ratio to maintain strip flatness is proposed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Shengwen Tu, Naoki Morita, Tsutomu Fukui, Kazuki Shibanuma
Summary: This study aimed to extend the finite element method to cope with elastic-plastic problems by introducing the s-version FEM. The s-version FEM, which overlays a set of local mesh with fine element size on the conventional FE mesh, simplifies domain discretisation and provides accurate numerical predictions. Previous applications of the s-version FEM were limited to elastic problems, lacking instructions for stress update in plasticity. This study presents detailed instructions and formulations for addressing plasticity problems with the s-version FEM and analyzes a stress concentration problem with linear/nonlinear material properties.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bo Fan, Zhongmin Wang
Summary: A 3D rotating hyperelastic composite REF model was proposed to analyze the influence of tread structure and rotating angular speed on the vibration characteristics of radial tire. Nonlinear dynamic differential equations and modal equations were established to study the effects of internal pressure, tread pressure sharing ratio, belt structure, and rotating angular speed on the vibration characteristics.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
X. W. Chen, Z. Q. Yue, Wendal Victor Yue
Summary: This paper examines the axisymmetric problem of a flat mixed-mode annular crack near and parallel to an arbitrarily graded interface in functionally graded materials (FGMs). The crack is modeled as plane circular dislocation loop and an efficient solution for dislocation in FGMs is used to calculate the stress field at the crack plane. The analytical solutions of the stress intensity factors are obtained and numerical study is conducted to investigate the fracture mechanics of annular crack in FGMs.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xumin Guo, Jianfei Gu, Hui Li, Kaihua Sun, Xin Wang, Bingjie Zhang, Rangwei Zhang, Dongwu Gao, Junzhe Lin, Bo Wang, Zhong Luo, Wei Sun, Hui Ma
Summary: In this study, a novel approach combining the transfer matrix method and lumped parameter method is proposed to analyze the vibration response of aero-engine pipelines under base harmonic and random excitations. The characteristics of the pipelines are investigated through simulation and experiments, validating the effectiveness of the proposed method.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xiangyu Sha, Aizhong Lu, Ning Zhang
Summary: This paper investigates the stress and displacement of a layered soil with a fractional-order viscoelastic model under time-varying loads. The correctness of the solutions is validated using numerical methods and comparison with existing literature. The research findings are of significant importance for exploring soil behavior and its engineering applications under time-varying loads.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Thuy Dong Dang, Thi Kieu My Do, Minh Duc Vu, Ngoc Ly Le, Tho Hung Vu, Hoai Nam Vu
Summary: This paper investigates the nonlinear torsional buckling of corrugated core sandwich toroidal shell segments with functionally graded graphene-reinforced composite (FG-GRC) laminated coatings in temperature change using the Ritz energy method. The results show the significant beneficial effects of FG-GRC laminated coatings and corrugated core on the nonlinear buckling responses of structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Zhihao Zhai, Chengbiao Cai, Qinglai Zhang, Shengyang Zhu
Summary: This paper investigates the effect of localized cracks induced by environmental factors on the dynamic performance and service life of ballastless track in high-speed railways. A mathematical approach for forced vibrations of Mindlin plates with a side crack is derived and implemented into a train-track coupled dynamic system. The accuracy of this approach is verified by comparing with simulation and experimental results, and the dynamic behavior of the side crack under different conditions is analyzed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
James Vidler, Andrei Kotousov, Ching-Tai Ng
Summary: The far-field methodology, developed by J.C. Maxwell, is utilized to estimate the effective third order elastic constants of composite media containing random distribution of spherical particles. The results agree with previous studies and can be applied to homogenization problems in other fields.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Kim Q. Tran, Tien-Dat Hoang, Jaehong Lee, H. Nguyen-Xuan
Summary: This study presents novel frameworks for graphene platelets reinforced functionally graded triply periodic minimal surface (GPLR-FG-TPMS) plates and investigates their performance through static and free vibration analyses. The results show that the mass density framework has potential for comparing different porous cores and provides a low weight and high stiffness-to-weight ratio. Primitive plates exhibit superior performance among thick plates.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bence Hauck, Andras Szekrenyes
Summary: This study explores several methods for computing the J-integral in laminated composite plate structures with delamination. It introduces two special types of plate finite elements and a numerical algorithm. The study presents compact formulations for calculating the J-integral and applies matrix multiplication to take advantage of plate transition elements. The models and algorithms are applied to case studies and compared with analytical and previously used finite element solutions.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Wu Ce Xing, Jiaxing Wang, Yan Qing Wang
Summary: This paper proposes an effective mathematical model for bolted flange joints to study their vibration characteristics. By modeling the flange and bolted joints, governing equations are derived. Experimental studies confirm that the model can accurately predict the vibration characteristics of multiple-plate structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Pingchao Yu, Li Hou, Ke Jiang, Zihan Jiang, Xuanjun Tao
Summary: This paper investigates the imbalance problem in rotating machinery and finds that mass imbalance can induce lateral-torsional coupling vibration. By developing a model and conducting detailed analysis, it is discovered that mass imbalance leads to nonlinear time-varying characteristics and there is no steady-state torsional vibration in small unbalanced rotors. Under largely unbalanced conditions, both resonant and unstable behavior can be observed, and increasing lateral damping can suppress instability and reduce lateral amplitude in the resonance region.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Yong Cao, Ziwen Guo, Yilin Qu
Summary: This paper investigates the mechanically induced electric potential and charge redistribution in a piezoelectric semiconductor cylindrical shell. The results show that doping levels can affect the electric potentials and mechanical displacements, and alter the peak position of the zeroth-order electric potential. The doping level also has an inhibiting effect on the first natural frequency. These findings are crucial for optimizing the design and performance of cylindrical shell-shaped sensors and energy harvesters.
APPLIED MATHEMATICAL MODELLING
(2024)