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Article
Publication date: 24 September 2021

Xue Deng and Yingxian Lin

The weighted evaluation function method with normalized objective functions is used to transform the proposed multi-objective model into a single objective one, which reflects the…

106

Abstract

Purpose

The weighted evaluation function method with normalized objective functions is used to transform the proposed multi-objective model into a single objective one, which reflects the investors' preference for returns, risks and social responsibility by adjusting the weights. Finally, an example is given to illustrate the solution steps of the model and the effectiveness of the algorithm.

Design/methodology/approach

Based on the possibility theory, assuming that the future returns of each asset are trapezoidal fuzzy numbers, a mean-variance-Yager entropy-social responsibility model is constructed including piecewise linear transaction costs and risk-free assets. The model proposed in this paper includes six constraints, the investment proportion sum, the non-negativity proportion, the ceiling and floor, the pre-assignment, the cardinality and the round lot constraints. In addition, considering the special round lot constraint, the proposed model is transformed into an integer programming problem.

Findings

The effects of different constraints and transaction costs on the effective frontier of the portfolio are analyzed, which not only assists investors to make decisions close to their expectations by setting appropriate parameters but also provides constructive suggestions through the overall performance of each asset.

Originality/value

There are two improvements in the improved particle swarm optimization algorithm: one is that the complex constraints are specifically satisfied by using a renewable 0–1 random constraint matrix and random scaling factors instead of fixed ones; the other is eliminating the particles with poor fitness and randomly adding some new particles that satisfy all the constraints to achieve the goal of global search as much as possible.

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Article
Publication date: 29 June 2021

Xue Deng, Xiaolei He and Cuirong Huang

This paper proposes a fuzzy random multi-objective portfolio model with different entropy measures and designs a hybrid algorithm to solve the proposed model.

155

Abstract

Purpose

This paper proposes a fuzzy random multi-objective portfolio model with different entropy measures and designs a hybrid algorithm to solve the proposed model.

Design/methodology/approach

Because random uncertainty and fuzzy uncertainty are often combined in a real-world setting, the security returns are considered as fuzzy random numbers. In the model, the authors also consider the effects of different entropy measures, including Yager's entropy, Shannon's entropy and min-max entropy. During the process of solving the model, the authors use a ranking method to convert the expected return into a crisp number. To find the optimal solution efficiently, a fuzzy programming technique based on artificial bee colony (ABC) algorithm is also proposed.

Findings

(1) The return of optimal portfolio increases while the level of investor risk aversion increases. (2) The difference of the investment weights of the optimal portfolio obtained with Yager's entropy are much smaller than that of the min–max entropy. (3) The performance of the ABC algorithm on solving the proposed model is superior than other intelligent algorithms such as the genetic algorithm, differential evolution and particle swarm optimization.

Originality/value

To the best of the authors' knowledge, no effect has been made to consider a fuzzy random portfolio model with different entropy measures. Thus, the novelty of the research is constructing a fuzzy random multi-objective portfolio model with different entropy measures and designing a hybrid fuzzy programming-ABC algorithm to solve the proposed model.

Details

Engineering Computations, vol. 39 no. 2
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 12 October 2020

Xue Deng and Weimin Li

This paper aims to propose two portfolio selection models with hesitant value-at-risk (HVaR) – HVaR fuzzy portfolio selection model (HVaR-FPSM) and HVaR-score fuzzy portfolio…

205

Abstract

Purpose

This paper aims to propose two portfolio selection models with hesitant value-at-risk (HVaR) – HVaR fuzzy portfolio selection model (HVaR-FPSM) and HVaR-score fuzzy portfolio selection model (HVaR-S-FPSM) – to help investors solve the problem that how bad a portfolio can be under probabilistic hesitant fuzzy environment.

Design/methodology/approach

It is strictly proved that the higher the probability threshold, the higher the HVaR in HVaR-S-FPSM. Numerical examples and a case study are used to illustrate the steps of building the proposed models and the importance of the HVaR and score constraint. In case study, the authors conduct a sensitivity analysis and compare the proposed models with decision-making models and hesitant fuzzy portfolio models.

Findings

The score constraint can make sure that the portfolio selected is profitable, but will not cause the HVaR to decrease dramatically. The investment proportions of stocks are mainly affected by their HVaRs, which is consistent with the fact that the stock having good performance is usually desirable in portfolio selection. The HVaR-S-FPSM can find portfolios with higher HVaR than each single stock and has little sacrifice of extreme returns.

Originality/value

This paper fulfills a need to construct portfolio selection models with HVaR under probabilistic hesitant fuzzy environment. As a downside risk, the HVaR is more consistent with investors’ intuitions about risks. Moreover, the score constraint makes sure that undesirable portfolios will not be selected.

Details

Engineering Computations, vol. 38 no. 5
Type: Research Article
ISSN: 0264-4401

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Book part
Publication date: 24 April 2023

Namhyun Kim, Patrick Wongsa-art and Ian J. Bateman

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative…

Abstract

In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.

Details

Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications
Type: Book
ISBN: 978-1-83753-212-4

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Article
Publication date: 23 May 2023

Shiyuan Yang, Debiao Meng, Hongtao Wang, Zhipeng Chen and Bing Xu

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile…

187

Abstract

Purpose

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

Design/methodology/approach

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

Findings

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Originality/value

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

Details

International Journal of Structural Integrity, vol. 14 no. 3
Type: Research Article
ISSN: 1757-9864

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Article
Publication date: 19 August 2010

Ziyi Wei

Since China initiated its “go global” policy that promotes its overseas investment, China’s Outward Foreign Direct Investment (OFDI) has increased almost twenty times during the…

2687

Abstract

Since China initiated its “go global” policy that promotes its overseas investment, China’s Outward Foreign Direct Investment (OFDI) has increased almost twenty times during the last 10 years, reaching $55.9 billion in 2008. The issue of internationalization of Chinese OFDI has attracted increasing attention of researchers from a business perspective. This article systematically reviews the previous studies on overseas investments by Chinese MNEs and discusses the characteristics of Chinese internationalization behavior at both firm level and country level. The internationalization of Chinese companies cannot be understood as a simple game of “catch up” with established MNEs, and more firm‐level empirical studies should be carried out on how these characteristics influence firms’ strategic decisions.

Details

Multinational Business Review, vol. 18 no. 3
Type: Research Article
ISSN: 1525-383X

Keywords

Available. Content available
Article
Publication date: 5 September 2023

Shiyuan Yang, Debiao Meng, Yipeng Guo, Peng Nie and Abilio M.P. de Jesus

In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper…

265

Abstract

Purpose

In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

Design/methodology/approach

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

Findings

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

Originality/value

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

Details

International Journal of Structural Integrity, vol. 14 no. 5
Type: Research Article
ISSN: 1757-9864

Keywords

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Article
Publication date: 3 August 2015

Zhengxin Wang and Lingling Pei

Although the Nash nonlinear grey Bernoulli model (NNGBM(1, 1)) is incomparable with respect to its flexibility over traditional grey models, errors are still inevitable in…

1209

Abstract

Purpose

Although the Nash nonlinear grey Bernoulli model (NNGBM(1, 1)) is incomparable with respect to its flexibility over traditional grey models, errors are still inevitable in forecasting. The purpose of this paper is to propose a Fourier residual modified Nash nonlinear grey Bernoulli model (FNNGBM(1, 1)) and use it to forecast the nonlinear time series of the international trade of Chinese high-tech products.

Design/methodology/approach

A Fourier series is used to modify the forecasting residual of the NNGBM(1, 1) model, so as to improve its forecasting ability. The parameters optimization of FNNGBM(1, 1) is formulated as a combinatorial optimization problem and is solved collectively using the concept of Nash equilibrium.

Findings

The simulation and practical application to fluctuation data both prove that FNNGBM(1, 1) could offer a more precise forecast than NNGBM(1, 1) and the Fourier residual GM(1, 1) (FGM(1, 1)). The import/export data of Chinese high-tech products will maintain rapid growth, with corresponding trade balance enlargement; however, there will be a concomitant decrease in the trade specialization coefficient.

Research limitations/implications

This study is deliberately general in its scope and outlook: its focus is mainly on the overall condition of Chinese high-tech products trade. Future research is recommended to analyze specific industrial trade sectors and extraneous influencing factors.

Originality/value

An effective method is proposed to enhance the accuracy of NNGBM(1, 1) model in forecasting a small sample, nonlinear time series.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 28 May 2024

Xiaohu Wen, Xiangkang Cao, Xiao-ze Ma, Zefan Zhang and Zehua Dong

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

99

Abstract

Purpose

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

Design/methodology/approach

A kind of micro-nano hydrophobic ternary microparticles was fabricated from SiO2/halloysite nanotubes (HNTs) and recycled concrete powders (RCPs), which was then mixed with sodium silicate and silane to form an inorganic slurry. The slurry was further sprayed on the concrete surface to construct a superhydrophobic coating (SHC). Transmission electron microscopy and energy-dispersive X-ray spectroscopy mappings demonstrate that the nano-sized SiO2 has been grafted on the sub-micron HNTs and then further adhered to the surface of micro-sized RCP, forming a kind of superhydrophobic particles (SiO2/HNTs@RCP) featured of abundant micro-nano hierarchical structures.

Findings

The SHC surface presents excellent superhydrophobicity with the water contact angle >156°. Electrochemical tests indicate that the corrosion rate of mild steel rebar in coated concrete reduces three-order magnitudes relative to the uncoated one in 3.5% NaCl solution. Water uptake and chloride ion (Cl-) diffusion tests show that the SHC exhibits high H2O and Cl- ions barrier properties thanks to the pore-sealing and water-repellence properties of SiO2/HNTs@RCP particles. Furthermore, the SHC possesses considerable mechanical durability and outstanding self-cleaning ability.

Originality/value

SHC inhibits water uptake, Cl- diffusion and rebar corrosion of concrete, which will promote the sustainable application of concrete waste in anti-corrosive concrete projects.

Details

Anti-Corrosion Methods and Materials, vol. 71 no. 5
Type: Research Article
ISSN: 0003-5599

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Article
Publication date: 9 January 2025

Debiao Meng, Peng Nie, Shiyuan Yang, Xiaoyan Su and Chengbo Liao

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea…

35

Abstract

Purpose

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

Design/methodology/approach

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

Findings

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

Originality/value

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.

Details

International Journal of Structural Integrity, vol. 16 no. 1
Type: Research Article
ISSN: 1757-9864

Keywords

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