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As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.

To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.

This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.

The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.

A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.

The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

The publication of Capital in the Twenty-First Century by Piketty (2014) propelled the debate about the prospects of the evolution of income and wealth inequalities in this century. One of the main controversies is about the effects on the income and wealth inequalities of a decrease in the growth rate g. In Piketty (2014), it is claimed that a decrease in g will cause an increase in the wealth inequality, through an increase in the difference r−g, where r is the rate of return on capital. This claim was criticized by many authors. In this chapter, the author presents a neoclassical growth model with heterogeneous agents and uses it to shed more light on this issue. The author’s model generalizes and improves previous models introduced in Piketty and Zucman (2015) and in Aoki and Nirei (2016). The author also presents a result, relating income, wealth, and wage inequalities.

As a core rotating component of power machinery and working machinery, the rotor system is widely used in the fields of machinery, electric power and aviation. When the system operates at high speed, the system stability is of great importance. To enhance the system stability, squeeze film damper (SFD) is being installed in the rotor system to alleviate vibration. The purpose of this paper is to first classify the rotor system into two types, the dual rotor system and the single rotor system, and to comprehensively and specifically mention the method of generating the dynamic model. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range.

In this paper, first, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. Here, the dynamic model of the rotor system was derived in detail for the single rotor system and the dual rotor system with and without SFD. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. The sensitivity analysis of the unbalanced response was carried out to determine the design variables of the optimization design. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range.

SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system through sensitivity analysis of the unbalanced response. These three variables are basic factors affecting the amplitude of the rotor system with SFD.

In the existing studies, only a dynamic model of a single rotor system with SFD was created, and the characteristic values of pure SFD were selected as optimization variables and optimization design was carried out. But in this study, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. In addition, optimization design variables were selected and optimized design was performed through sensitivity analysis on the unbalanced response of factors affecting the vibration characteristics of the rotor system.

The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

The purpose of this paper is to propose a semiparametric estimator for the tail index of Pareto-type random truncated data that improves the existing ones in terms of mean square error. Moreover, we establish its consistency and asymptotic normality.

To construct a root mean squared error (RMSE)-reduced estimator of the tail index, the authors used the semiparametric estimator of the underlying distribution function given by Wang (1989). This allows us to define the corresponding tail process and provide a weak approximation to this one. By means of a functional representation of the given estimator of the tail index and by using this weak approximation, the authors establish the asymptotic normality of the aforementioned RMSE-reduced estimator.

In basis on a semiparametric estimator of the underlying distribution function, the authors proposed a new estimation method to the tail index of Pareto-type distributions for randomly right-truncated data. Compared with the existing ones, this estimator behaves well both in terms of bias and RMSE. A useful weak approximation of the corresponding tail empirical process allowed us to establish both the consistency and asymptotic normality of the proposed estimator.

A new tail semiparametric (empirical) process for truncated data is introduced, a new estimator for the tail index of Pareto-type truncated data is introduced and asymptotic normality of the proposed estimator is established.

To find the reliability characteristics of repairable weighted (u, v)- out-of-(x, y) system using the interval valued universal generating function (IUGF).

In this paper (u, v)-out-of-(x, y) system is an extension of the k-out-of-n system. Here, the interval valued universal generating function (UGF) is present and the corresponding operators are defined.

The present paper proposes a interval valued universal generating function (IUGF) to compute the reliability indices of the considered system. The current study investigates the reliability and sensitivity of the proposed system with respect to system parameters by applying Markov process with the help of the interval valued UGF approach.

In this work, the considered system, i.e. repairable weighted (u, v)-of-the- (x, y) is the extension of k-out-of-n system for the assessment of reliability characteristics using the interval valued UGF.