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Article
Publication date: 9 July 2018

Changjin Xu and Peiluan Li

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying…

143

Abstract

Purpose

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Design/methodology/approach

The differential inequality theory and some novel mathematical analysis techniques are applied.

Findings

A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.

Practical implications

It plays an important role in designing the neural networks.

Originality/value

The obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 11 no. 3
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 7 June 2018

Phongsatorn Saisutjarit and Takaya Inamori

The purpose of this paper is to investigate the time optimal trajectory of the multi-tethered robot (MTR) on a large spinning net structures in microgravity environment.

149

Abstract

Purpose

The purpose of this paper is to investigate the time optimal trajectory of the multi-tethered robot (MTR) on a large spinning net structures in microgravity environment.

Design/methodology/approach

The MTR is a small space robot that uses several tethers attached to the corner-fixed satellites of a spinning net platform. The transition of the MTR from a start point to any arbitrary designated points on the platform surface can be achieved by controlling the tethers’ length and tension simultaneously. Numerical analysis of trajectory optimization problem for the MTR is implemented using the pseudospectral (PS) method.

Findings

The globally time optimal trajectory for MTR on a free-end spinning net platform can be obtained through the PS method.

Research limitations/implications

The analysis in this paper is limited to a planar trajectory and the effects caused by attitude of the MTR will be neglected. To make the problem simple and to see the feasibility in the general case, in this paper, it is assumed there are no any limitations of mechanical hardware constraints such as the velocity limitation of the robot and tether length changing constraint, while only geometrical constraints are considered.

Practical implications

The optimal solution derived from numerical analysis can be used for a path planning, guidance and navigation control. This method can be used for more efficient on-orbit autonomous self-assembly system or extravehicular activities supports which using a tether-controlled robot.

Originality/value

This approach for a locomotion mechanism has the capability to solve problems of conventional crawling type robots on a loose net in microgravity.

Details

Aircraft Engineering and Aerospace Technology, vol. 90 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Available. Open Access. Open Access
Article
Publication date: 30 June 2010

Hwa-Joong Kim, Eun-Kyung Yu, Kwang-Tae Kim and Tae-Seung Kim

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the…

194

Abstract

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the problem with two practical considerations: minimum order size and lost sales. The minimum order size is the minimum amount of items that should be purchased and lost sales involve situations in which sales are lost because items are not on hand or when it becomes more economical to lose the sale rather than making the sale. The objective is to minimize the costs of ordering, item , inventory holding and lost sale over the planning horizon. To solve the problem, we suggest a heuristic algorithm by considering trade-offs between cost factors. Computational experiments on randomly generated test instances show that the algorithm quickly obtains near-optimal solutions.

Details

Journal of International Logistics and Trade, vol. 8 no. 1
Type: Research Article
ISSN: 1738-2122

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Article
Publication date: 1 December 1998

Fuyong Lin and T.C. Edwin Cheng

Based on several new concepts, this paper mathematically deduces a new model of general systems, namely, the structural model of general systems. By its mathematical analysis, the…

237

Abstract

Based on several new concepts, this paper mathematically deduces a new model of general systems, namely, the structural model of general systems. By its mathematical analysis, the principles and laws of general systems can be mathematically achieved, which can not only help scientists achieve a better understanding and control of complex systems in nature and society but also be applied to solve particular scientific problems, and thus a problem‐oriented and mathematically expressed general systems theory, namely, the structural theory of general systems, would be achieved.

Details

Kybernetes, vol. 27 no. 9
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 5 February 2025

Essaid Aourir and Hojatollah Laeli Dastjerdi

This contribution investigates the numerical solution of Volterra integral equations with auto-convolution of the third kind (AVIE). The numerical method applied in this…

6

Abstract

Purpose

This contribution investigates the numerical solution of Volterra integral equations with auto-convolution of the third kind (AVIE). The numerical method applied in this investigation employs a collocation method based on the moving least squares (MLS) approximation. The MLS approximation is an effective way of approximating an unknown function by taking a disordered dataset. This method is a mesh-free approach since it does not require background interpolation or approximation cells, and is independent of domain geometry. The proposed method reduces the solution of third-kind AVIEs to the solution of systems of algebraic equations. By employing the Gauss–Legendre integration formula, we can estimate all the integrals of these equations. The applicability and validity of this method are demonstrated by numerical experiments, and its efficiency and robustness are proven by comparison with existing methods.

Design/methodology/approach

The numerical method applied in this study uses a collocation method based on moving least squares (MLS) approximation. This method is a mesh-free approach since it requires no background interpolation or approximation cells and is independent of domain geometry. Using the Gauss–Legendre integration formula, we can estimate all the integrals of these equations.

Findings

The authors declare that they have no known competing financial interests.

Originality/value

The manuscript has not been copyrighted or published previously and is not under consideration for publication elsewhere.

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Article
Publication date: 28 January 2025

Xuan Yang, Hao Luo, Xinyao Nie and Xiangtianrui Kong

Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding…

14

Abstract

Purpose

Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding of complex systems it encapsulates can be displayed through formalization methods. This study seeks to develop a methodology for formalizing tacit knowledge in a dynamic delivery system.

Design/methodology/approach

This study employs a structured survey to gather experiential knowledge from dispatchers engaged in last-mile delivery operations. This knowledge is then formalized using a value function approximation approach, which transforms tacit insights into structured inputs for dynamic decision-making. We apply this methodology to optimize delivery operations in an online-to-offline pharmacy context.

Findings

The raw system feature data are not strongly correlated with the system’s development trends, making them ineffective for guiding dynamic decision-making. However, the system features obtained through preprocessing the raw data increase the predictiveness of dynamic decisions and improve the overall effectiveness of decision-making in delivery operations.

Research limitations/implications

This research provides a foundational framework for studying sequential dynamic decision problems, highlighting the potential for improved decision quality and system optimization through the formalization and integration of tacit knowledge.

Practical implications

This approach proposed in this study offers a method to preserve and formalize critical operational expertise. By embedding tacit knowledge into decision-making systems, organizations can enhance real-time responsiveness and reduce operational costs.

Originality/value

This study presents a novel approach to integrating tacit knowledge into dynamic decision-making frameworks, demonstrated in a real-world last-mile delivery context. Unlike previous research that focuses primarily on explicit data-driven methods, our approach leverages the implicit, experience-based insights of operational staff, leading to more informed and effective decision-making strategies.

Details

Industrial Management & Data Systems, vol. 125 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

Available. Open Access. Open Access
Article
Publication date: 4 December 2024

Vighneswara Swamy and Vijayakumar Narayanamurthy

This article explores the effects of monetary policy rates and interest rate structures on bank profitability.

65

Abstract

Purpose

This article explores the effects of monetary policy rates and interest rate structures on bank profitability.

Design/methodology/approach

We studied 65 Indian commercial banks over time, including economic cycles, consolidation and the Great Financial Crisis. We categorized commercial banks by ownership (public, private or foreign) and predicted how they will react to monetary policy changes. We employed the instrumental variable estimate approach and panel Granger causality tests to give evidence of the direction of causation in the monetary policy and bank performance nexus.

Findings

Private and international banks, we believe, are more sensitive to changes in reserve requirements because they are more effective at maintaining statutory reserves. Private and international banks are more susceptible to repo rate fluctuations than state banks. In contrast, public banks are more sensitive to bank rates because they are more likely than private and international banks to use the bank rate window of accommodation.

Originality/value

We studied the impact of monetary policy rates on bank performance within the banking-dominated financial system of an emerging economy – a focus that has not been previously explored. There has been little research into the connection between monetary policy rates and bank performance in emerging markets, notably in India.

Details

Journal of Economics, Finance and Administrative Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2077-1886

Keywords

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Article
Publication date: 20 November 2024

Aysegul Erem Halilsoy and Funda Iscioglu

This study evaluates the reliability of a multi-state system (MSS) with n components, each having two s-dependent components via copulas.

40

Abstract

Purpose

This study evaluates the reliability of a multi-state system (MSS) with n components, each having two s-dependent components via copulas.

Design/methodology/approach

The study employs copula functions to model dependencies between components in an MSS. Specifically, it analyzes a (1,1)-out-of-n three-state system using Frank and Clayton copulas for reliability evaluation. A simulation-based case study of a micro-inverter solar panel system is also conducted using the Farlie–Gumbel–Morgenstern (FGM) copula.

Findings

The study finds that incorporating component dependencies significantly impacts the reliability of multi-state systems. Using Frank and Clayton copulas, the analysis shows how dependency structures alter system performance compared to independent models. The case study on a micro-inverter solar panel system, using the FGM copula, demonstrates that real-world systems with dependent components exhibit different performances. Also some effects of dependence parameters on the performance characteristics of the system such as mean residual lifetime and mean past lifetime are also examined.

Originality/value

This study is original in its use of copula functions to evaluate the performance of multi-state systems, particularly focusing on a (1,1)-out-of-n three-state system with dependent components. By applying Frank and Clayton copulas, the research advances reliability analysis by considering component dependencies, often overlooked in traditional models. Additionally, a case study on a micro-inverter solar panel system using the FGM copula highlights the practical application of these methods.

Details

Engineering Computations, vol. 42 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 21 October 2024

Marke Geisy da Silva Dantas, Thadeu Gasparetto, Alexandro Barbosa and Luciano Sampaio

This paper analyses the efficiency and productivity of Brazilian football clubs in the post-world cup 2014 period (2014–2022) using a network dynamic DEA-Malmquist model.

54

Abstract

Purpose

This paper analyses the efficiency and productivity of Brazilian football clubs in the post-world cup 2014 period (2014–2022) using a network dynamic DEA-Malmquist model.

Design/methodology/approach

Financial and sporting efficiency and productivity in Brazilian football clubs.

Findings

The financial division’s average efficiency is higher than that of the sporting division and overall efficiency from 2014 to 2022. Fourteen clubs exhibited increased productivity during this period. Regression models revealed a statistically significant positive relationship between the debt ratio and DEA dependent variable models at a 1% significance level and a significant negative relationship with the three Malmquist dependent variable models. Additionally, the models identified a statistically significant relationship with the “Covid” (2020 years) variable across all models.

Practical implications

Our findings suggest that increased expenditures can lead to higher liabilities, reducing the ability to afford high-quality players and thus diminishing overall club value. Additionally, the inefficiencies observed among some of the largest football clubs reveal room for improvement in both financial and sportive aspects.

Originality/value

This is the first study to investigate efficiency and productivity in two dimensions for Brazilian football clubs, incorporating an analysis of productivity over an extended period and examining the impact of debt and other determinants on club performance.

Details

Managerial Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0307-4358

Keywords

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Article
Publication date: 21 October 2024

Safeer Ullah, Jiang Yushi and Miao Miao

This study aims to inspect the impact of US climate policy uncertainty (CPU) on the economic growth of Asian countries with the moderating role of crude oil price (COP) changes.

56

Abstract

Purpose

This study aims to inspect the impact of US climate policy uncertainty (CPU) on the economic growth of Asian countries with the moderating role of crude oil price (COP) changes.

Design/methodology/approach

The Im-Pesaran Sin and Fisher-type tests are used for stationarity check, while Kao and Pedroni tests are used for cointegration analysis. The Hausman test is applied for model selection, where pooled mean group autoregressive distributed lag (PMG/ARDL) has been selected and applied. Besides, the fully modified ordinary least squares is also used for robustness analysis. Additionally, the literature review and descriptive statistics have been used.

Findings

The main findings disclosed that US CPU negatively impacted the economic growth of Asian economies with high significance in the long run whereas insignificant in the short run. The results further concluded that COP positively affected economic growth both in the short and long run. Furthermore, the results also revealed that COP significantly and positively moderates the relationship between CPU and COP in the long and short run.

Originality/value

The study is the first of its kind to examine the impact of the US CPU on the economic growth of Asian economies. Second, it further revealed the moderating role of COP between US CPU and economic growth. Third, a large panel of data from Asian countries has been considered. Fourth, the study adds to the current literature by using the PMG/ARDL model to determine the impact of US CPU on economic growth. Additionally, this study focuses on the US CPU because it is a developed country playing a significant role in energy and climate issues, and has been very uncertain.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

Keywords

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