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The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

To improve the operational efficiency and intelligence of live operation robots in dynamic-unstructured operation environments, this paper aims to propose a fuzzy logic-based method for the autonomous search and visual localization control of a manipulator end effector applied to a drainage plate bolt on a high-voltage transmission line. The proposed approach is based on a four-way video image information output from a dual-operation manipulator.

First, based on the structural characteristics of the drainage line, an autonomous search method for the drainage plate bolt and a mapping relationship between the autonomous search control parameters and the relative posture of the operation manipulator-drainage line are proposed. The posture control parameters of the dual manipulators can then be obtained, and a two-dimensional fuzzy controller is designed with the posture offset distance and the posture offset angle as its input signals. This enables the localization control of the bolt and nut alignment to be realized through a visual process.

The proposed fuzzy control algorithm is used for bolt location control, and its performance is compared with that of the conventional approach. The simulation results indicate that the fuzzy control algorithm greatly improves the localization accuracy and operational efficiency of live operation robots.

Field operation experiments on actual transmission lines verify that the fuzzy control-based visual localization control of the robot manipulator has great engineering practicality. Therefore, the proposed method further improves operational intelligence compared with conventional algorithms.

The extant literature highlights the notable lack of a consensus among operations and supply chain management scholars regarding the theoretical underpinnings and associated empirical evidence for the performance impact of supply chain quality management (SCQM) practices on quality. The purpose of this paper is to redress this imbalance in the literature through empirical examination of the relationship between SCQM practices and quality performance outcomes.

In accordance with the research aim, a quantitative approach was adopted, and a multi-item scale Web-based survey was designed to collect primary data. A total number of 325 questionnaires were collected from a sample of UK-based manufacturing companies. Factor analysis, internal consistency and multivariate regressions were used to validate the multi-item scale and test the hypotheses.

The findings confirm the proposed hypotheses and reveal statistically significant results for the performance impact of SCQM practices on quality at an aggregate level. However, the results of the individual level analysis of SCQM practices appear to vary from practice to practice. Of various SCQM practices, customer focus with the highest beta value (i.e. ß = 0.303; t-value = 6.120; p = 0.000) was found to have the greatest impact on quality performance.

The findings encourage managers to place high priority on both inter-firm and intra-firm relationships as prerequisites for achieving superior quality performance. The propositions and the results of the study provide managers with some guidelines about effective management of upstream, midstream and downstream supply chain networks and awareness of the potential synergies arising from the combined effects of SCQM practices that could bring about desired quality performance outcomes across the entire supply chain network.

Real and sustainable quality performance often requires an equal focus on both intra- and inter-firm relationships among supply chain partners. Therefore, effective management of quality across the entire supply chain is deemed essential if a firm is to smoothly supply high-quality products and services to customers. But little research has been devoted to understanding conceptual underpinnings of SCQM as well as empirical support and validation for the conceptualisation and measurement of SCQM practices. Based on the insights gained from social network theory, this paper makes an attempt to address this gap and examine the impact of SCQM practices on quality performance.

The purpose of this paper is to propose a new acceleration/deceleration (acc/dec) algorithm for motion profiles. The motion efficiency, flexibility of the motion profiles and the residual vibration of the movement are discussed in this paper.

A dynamics model is developed to assess the residual vibration of these two kinds of motion profile. And a Simulink model is created to assess the motion efficiency and flexibility of the motion profiles with the proposed acc/dec algorithm.

Considering the flexibility of trigonometric motion profiles and the higher motion efficiency of S-curve motion profiles, the authors add the polynomial parts into the jerk profile of the cosine function acc/dec algorithm to hold the jerk when it reaches the maximum so that the motion efficiency can increase and decrease residual vibration at the same time. And the cyclical parameter k shows the decisive factor for the flexibility of trigonometric motion profiles.

Comparing with the traditional motion profiles, the proposed motion profiles have higher motion efficiency and excite less residual vibration. The acc/dec algorithm proposed in this paper is useful for the present motion control and servo system.

Given the scarcity of data during the early stages of the COVID-19 pandemic in China, the decision-making for non-pharmaceutical policies was mostly based on insufficient evidence. The purpose of this study is to assess the effectiveness of these policies, such as lockdown and government subsidies, on rural households and identify policy implications for China and other countries in dealing with pandemics.

The authors survey 2,408 rural households by telephone from 101 counties across 17 provinces in China during the first stage of the pandemic (March 2020). The authors use the ordered probit model and linear regression model to study the overall impact of policies and then use the quantile regression model and sub-sample regression method to study the heterogeneity of the effects of government policies.

The authors find that logistics disruption due to lockdown negatively affected rural households. Obstructed logistics is associated with a more significant loss for high-income households, while its impact on the loss expectation of low-income households is more severe. Breeding and other industries such as transport and sales suffer more from logistics than cultivation. The impact of logistics on intensive agricultural entities is more serious than that on professional farms. The government subsidy is more effective at reducing loss for low-income households. Lockdown and government subsidies have shown heterogeneous impacts on rural households.

The overall economic losses experienced by rural households in the early stages of the pandemic are controllable. The government policies of logistics and subsidies should target specific groups.

The authors evaluate the economic impacts of lockdown and government subsidies on rural households and show their heterogeneity among different groups. The authors further demonstrate the policy effectiveness in supporting rural households during the early stages of the pandemic and provide future policy guidance on major public health event.

First, the paper aims to explore the ability of the actor sitting on the structural hole to achieve the additional rent, which is modeled as the outcome of joint effect between the relational performances of two dyads (supplier–buyer and buyer–customer) within the triadic supply chains. Second, the paper seeks to empirically compare the value of additional rent among different structural hole states of triadic supply chains.

Building upon the theoretical tenets of social capital theory, complemented by the underpinnings of relational view, this research uses survey data gathered from the triadic supply chains in Europe. To conduct necessary processing, the multivariate statistical analyses have been performed.

The findings suggest that the rent is actually yielded by the actors bridging the structural hole in the triadic supply chain; however, its value, as evidenced in the study, is diverse regarding the specific structural hole state. More specifically, the highest value of rent is generated by the buyer establishing cooperative posture of both dyads in the triadic supply chains. The value of rent close to zero is revealed in the triadic supply chains with negative relational posture of both dyads. Interestingly, the lowest level of rent produced by the buyer from bridging the structural hole is reported with the triadic supply chains in which one dyad demonstrates a more cooperative relational posture, whereas the other one indicates an adversarial relational posture. Not only does this result suggest that there is no rent, but it even goes further to indicate a negative return (or loss) derived by the manufacturer in this group of triadic supply chains.

The study is limited to the relational posture, either strong or weak; therefore, it would be worthwhile to examine a wider spectrum of behaviors, based on the adversarial relationships, deprived of mutual trust, when both actors in a dyad act opportunistically and antagonistically. Moreover, regarding the research method used, the case study is usually deemed to be more appropriate to deeply grasp the complex issues of social behavior. Finally, caution should also be exercised while generalizing the results obtained from the research.

For practicing supply chain managers, this study points that that it is likely that both actors collaborating with the buyer (the supplier and the customer) also enjoy additional benefits offered by the rent. Importantly for managers, regardless of the effort made by the focal actor, the careless attitude and independence of suppliers and customers may make it hard or even impossible for the buyer to establish triads that include relationships of high quality.

In terms of social implications, this study brings to the fore that not only are the buyers driven by self-interest but they may be also guided by ethical and social rules when interacting with suppliers and customers in their triads. This research evidenced that the buyer in the triadic supply chain can act as the moderator that tends to simultaneously establish a strong relational posture to two other actors in such a way that the joint effect of relational performance generated by both dyads significantly contributes to the higher level of buyer’s individual performance.

The study investigates whether and how establishing relational posture of two dyads in the triadic supply chains can affect the additional rent for the buyer derived from bridging the structural hole.

This paper aims to present a new method, named as augmented polynomial dimensional decomposition (PDD) method, for robust design optimization (RDO) and reliability-based design optimization (RBDO) subject to mixed design variables comprising both distributional and structural design variables.

The method involves a new augmented PDD of a high-dimensional stochastic response for statistical moments and reliability analyses; an integration of the augmented PDD, score functions, and finite-difference approximation for calculating the sensitivities of the first two moments and the failure probability with respect to distributional and structural design variables; and standard gradient-based optimization algorithms.

New closed-form formulae are presented for the design sensitivities of moments that are simultaneously determined along with the moments. A finite-difference approximation integrated with the embedded Monte Carlo simulation of the augmented PDD is put forward for design sensitivities of the failure probability.

In conjunction with the multi-point, single-step design process, the new method provides an efficient means to solve a general stochastic design problem entailing mixed design variables with a large design space. Numerical results, including a three-hole bracket design, indicate that the proposed methods provide accurate and computationally efficient sensitivity estimates and optimal solutions for RDO and RBDO problems.

The purpose of this article is to present the idea of a T-spherical hesitant fuzzy set associated with probability and to develop an extended multi-attributive border approximation area comparison (MABAC) method under probabilistic T-spherical hesitant fuzzy (Pt-SHF) settings.

The authors define some basic operational laws for Pt-SHF sets (Pt-SHFSs) and a comparison method of two probabilistic T-spherical hesitant fuzzy numbers (Pt-SHFNs) is proposed. Moreover, some Pt-SHF aggregation operators and the multi-attributive border approximation area comparison (MABAC) method are established under Pt-SHF scenario to solve group decision making problems.

The developed Pt-SHF MABAC method for multi-attribute group decision making (MAGDM) can overcome the drawbacks of conventional MABAC method and limitations for decision makers, which they face while providing their assessment concerning any object.

Clearly, this paper is devoted to MABAC method, MAGDM and probabilistic T-spherical hesitant fuzzy set theory.

The approach established can be used in a variety of scenarios, including decision making, engineering, and economics. An explanatory example is illustrated which shows the superiority and effectiveness of our proposed technique.

If a T-spherical fuzzy MAGDM problem under the probabilistic scenario needs to be evaluated, the involvement of probabilities in fuzzy system will be lost because of no information. This work fills a gap in literature by establishing the notion of probabilistic t-spherical hesitant fuzzy set to deal with the ambiguity, uncertainty in decision making problems.

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).

To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.

To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.

Traditional risk assessment (RA) methodologies cannot model vagueness in risk and cannot prioritize corrective-preventive measures (CPMs) by considering effectiveness of those on risk types (RTs). These cannot combine and reflect accurately different subjective opinions and cannot be used in a linguistic manner. Risk factors (RFs) are assumed to have the same importance and interrelations between RFs are not considered. This study aims to overcome these disadvantages by combining fuzzy logic with multi-criteria decision-making in a dynamic manner.

This study proposes a novel three-stage fuzzy risk matrix-based RA integrating fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) and fuzzy multi-attributive border approximation area comparison (F-MABAC). At the first stage, importance weights of RFs are computed by F-DEMATEL. At the second stage, risk degrees of RTs are computed via using fuzzy risk matrix. At the third stage, CPMs are ranked by F-MABAC. Finally, a numerical example for RA in a warehouse is given.

Results show that developing instructions for material loading or unloading is the most important CPM and severity is the most important RF for the warehouse.

This study has originality in terms of having fuzzy dynamic structure. At first, RFs are assumed to be criteria sets then, RTs are assumed to be criteria set considering their risk degrees to rank CPMs in a fuzzy manner. Risk degrees of RTs are used for weights of RTs and effectiveness of CPMs are used for performance values of CPMs.