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Against the background of the global active pursuit of carbon neutrality, this paper uses the DY spillover index method to analyze the spillover network effects between carbon, fossil energy and financial markets. The research results show that the spillover effects between these three markets change over time, with an average spillover index of 25.30%, showing a significant mutual influence. Further analysis found that the EU carbon market plays an important role in spillover effects. Especially under the influence of extreme events, the spillover effects reach their peak. At this time, the degree of mutual influence between markets is as high as 60.01%. In addition, during the COVID-19 epidemic, the spillover effect of the EU carbon market on other markets also reached its maximum, indicating that the epidemic increased the contagion of cross-market risks and caused the carbon market to bear greater risks. The research results of this article have important guiding significance for environmental protection investment and emphasize the importance of formulating differentiated environmental protection policies in different time frames. Facing the dual challenges of global climate change and promoting the goal of carbon neutrality, governments and relevant institutions should pay close attention to changes in spillover effects between markets and timely adjust environmental protection policies to achieve maximum results. [ABSTRACT FROM AUTHOR]

• A system dynamics model is developed to visualize the process of value creation. • This study provides insight into the essence of digital transformation. • This study answeres how can enterprises create value via digital transformation. How do enterprises create value? In the digital economy era, digital transformation (DT) is an answer. How can enterprises create value using DT? This remains an important issue. This study develops a system dynamics (SD) model to scientifically answer this question. The SD model incorporates five subsystems–data, technology, talent, value, and environment–are defined as system boundary. The parameters of data subsystem, technical subsystem, talent subsystem, and environmental subsystem serve as imaginary dials that can be manipulated to observe the responds of the value subsystem. Causal loop diagrams (CLD) and stock and flow diagrams (SFD) are used to visualize the dynamic process of value creation in the context of DT. By observing the flow of elements within the system, the specific implementation paths and key driving factors for value creation through DT are identified. The results of numerical simulation shows the practical viability of the developed model. This SD model contributes to the current conversation about DT and value creation by responding to recent calls to demystify the 'black box' of DT. It also provides a new theoretical basis and empirical support for the study of the influencing factors and economic consequence of DT. [ABSTRACT FROM AUTHOR]

This paper presents a novel failure mode and effect analysis (FMEA) framework as a formal design method to ensure safety and reliability. FMEA is used to identify potential failure modes (FMs), and it is crucial to determine the weights of risk factors and prioritize FMs. In this work, we propose a comprehensive framework that integrates the Dempster-Shafer theory, best-worst method (BWM), stochastic multi-objective acceptability analysis (SMAA), and measurement of alternatives and ranking according to compromise solution (MARCOS) to address this problem. To capture the uncertainty caused by the loss of information, the Dempster-Shafer theory is applied for dealing with the uncertainty about risk factors and FMs in terms of linguistic information. Based on the comprehensive evidential preference interval vectors of risk factors constructed by Dempster-Shafer theory, an evidential BWM combined with SMAA is proposed to determine the optimal set of risk factor weights. Meanwhile, based on the constructed interval belief interval decision matrix of FMs to risk factors constructed by Dempster-Shafer theory, an evidential SMAA-MARCOS method is proposed for determining the risk priority of FMs. Further, we conduct a case study to evaluate the risk of equipment in an automobile manufacturing enterprise. A sensitivity and comparative analysis are also conducted to demonstrate the effectiveness and superiority of the proposed framework. • An evidential SMAA method is proposed to identify the best and worst risk factors. • An evidential BWM is proposed to determine the weights of risk factors. • An evidential SMAA-MARCOS method is proposed to rank FMs. • The FMEA framework using evidential BWM and SMAA-MARCOS method is proposed. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multi-criteria group decision-making (MCGDM) problems with incomplete weight information under T-spherical fuzzy environment. Firstly, motivated by the idea of the intuitionistic fuzzy interaction method, we propose some operation laws of T-spherical fuzzy numbers (T-SFNs), as well as some T-spherical fuzzy interaction aggregation operators, such as the T-spherical fuzzy weighted averaging interaction (T-SFWAI) operator, the T-spherical fuzzy weighted geometric interaction (T-SFWGI) operator, the T-spherical fuzzy ordered weighted interaction aggregation operators and the generalized T-spherical fuzzy interaction aggregation operators. Then, some desirable properties of the proposed T-SFWAI and T-SFWGI operators and some special cases of the generalized T-spherical fuzzy interaction aggregation operators are discussed in detail. Secondly, for the situations where the information about the weights of criteria is partly known or completely unknown, we establish two optimization models to determine the weights of criteria based on the maximizing deviation method and Lagrange function method, respectively. Thirdly, the traditional TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) approach is extended to solve MCGDM problem under the T-spherical fuzzy environment by defining the distance between T-SFNs, score function and accuracy function of T-spherical fuzzy number. Finally, a numerical example is given to illustrate the application of the extended TODIM approach, and further the sensitivity analysis and comparison analysis are carried out to demonstrate the influence of parameter on the final result and the effectiveness of the extended method. [ABSTRACT FROM AUTHOR]

This study explores the nexus between financial development, access to electricity, and CO2 emissions in Pakistan over the period from 1990 to 2015, incorporating the role of natural resources and population growth. We checked the stationarity of the data by using three different unit root tests (ADF, Phillip Pesaran, and DG‐FLS). Long‐ and short‐run elasticities have been determined through auto‐regressive distributive lag (ARDL) method. The empirical results confirmed that financial development and access to electricity increase CO2 emissions and deteriorate the environmental quality. In addition, the population growth is responsible for growing CO2 emissions in Pakistan, while natural resources have insignificant relation with CO2 emissions. Furthermore, bidirectional causality exists between population growth and natural resources, whereas unidirectional causality is detected among financial development and CO2 emissions, natural resources and population growth, and financial development and population growth. The newly developed findings suggest helpful policy implications to adequately address the issue of CO2 emissions without compromising economic development. [ABSTRACT FROM AUTHOR]

• Multi-granular linguistic distribution evidential reasoning method is proposed. • Incomplete and uncertain evaluation is handled in MCGDM problems. • A novel comparison method for linguistic distribution assessments is introduced. • Developed a transformation technique for multi-granular linguistic distribution. • Renewable energy project risk assessment is conducted. Nowadays, renewable energy projects have constantly been emphasized and the assessment of potential risks has been considered as an indispensable activity prior to implementation of projects. To carry out a reasonable assessment, multi-granular linguistic distribution assessments (LDAs), an effective and uncertainty representation tool, are adopted to express and quantify opinions based on personalized individual linguistic term sets. Specifically, this study develops a novel uncertain multiple criteria decision making approach, named multi-granular linguistic evidential reasoning method, which can handle incomplete and personalized preferences. A novel comparison method for LDAs is first put forward based on numerical characteristics, namely an expectation value and central moment. To fuse the multi-granular LDAs, a lossless transformation technique is further introduced and some of itsessential properties are discussed. Finally, a case study on renewable energy project risk assessment is discussed to verify the feasibility of the proposed method. Besides, sensitivity analysis is conducted to investigate the sequencing stability and comparative analysis is included to highlight the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

By combining picture fuzzy set and 2-tuple linguistic representation model, Wei et al. (Soft Comput 22(3):989–1002, 2018) proposed the concept of picture 2-tuple linguistic set and presented some operational laws of picture 2-tuple linguistic numbers (P2TLNs). On the basis of operational laws of P2TLNs, some picture 2-tuple linguistic aggregation operators have been further developed. However, some operational laws and results derived by aggregation operators proposed by Wei et al. (Soft Comput 22(3):989–1002, 2018) are conflict with definition of picture 2-tuple linguistic number (P2TLN). In this short note, we propose some novel operational laws of P2TLNs and develop one adjusted picture 2-tuple linguistic aggregation operator, i.e., the adjusted picture 2-tuple linguistic weighted averaging operator. [ABSTRACT FROM AUTHOR]

Generalized Heronian mean (GHM) is a useful aggregation operator with the characteristic of capturing the interrelationship of evaluation information. In this paper, we propose some new operators by combining the power average operator and the GHM operator under hesitant fuzzy linguistic environment, such as the hesitant fuzzy linguistic power generalized Heronian mean (HFLPGHM) operator, the hesitant fuzzy linguistic power generalized geometric Heronian mean (HFLPGGHM) operator, the hesitant fuzzy linguistic weighted power generalized Heronian mean (HFLWPGHM) operator and the hesitant fuzzy linguistic weighted power generalized geometric Heronian mean (HFLWPGGHM) operator. Then, some special cases of the proposed HFLPGHM and HFLPGGHM operators are discussed in detail. Furthermore, based on the proposed operators, we develop a novel method to solve multi-attribute group decision-making problem under hesitant fuzzy linguistic environment. Finally, a numerical example is given to illustrate the application of the developed method and a comparison analysis is also conducted, which further demonstrates the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

We create a generational patent citation tree to reveal the development of bogie technology in the high-speed rail industry. We cull the information in patent citations to reveal the generational development of bogie technology by analysing patent titles, patent publication dates and patent-granting regions. We then measure the development of bogie technology by calculating its technological development on-orbit rate and by mapping the stages of technological development and its regional diffusion. The results show that bogie technologies are in a period of sustained growth and this period of sustained growth will remain. Technological development is accelerating and this acceleration will persist, although the global dispersion of technology lags behind in scope and speed. [ABSTRACT FROM AUTHOR]

To date, type-2 fuzzy sets have attracted much more interest of the researchers, which are more capable to handle uncertain and imprecision information than type-1 fuzzy sets. Heronian mean is a classical mean aggregation operator which can effectively consider the interrelationships between various arguments. In this paper, we extend Heronian mean to trapezoidal interval type-2 fuzzy environment and present some aggregation operators, such as trapezoidal interval type-2 fuzzy generalized Heronian mean (TIT2FGHM) operator and trapezoidal interval type-2 fuzzy weighted generalized Heronian mean (TIT2FWGHM) operator. Then, we further discuss several desirable properties and particular cases when the parameters take diverse values in detail. Moreover, concerning multiple attribute group decision making problems in which the decision attributes are interdependent and the attribute values take the forms of interval type-2 fuzzy numbers, we propose a new approach based on TIT2FWGHM operator. Finally, we provide a numerical example of providers selection to illustrate the practicality and effectiveness of the proposed method and give a comparison analysis between the proposed method and existing methods. [ABSTRACT FROM AUTHOR]

Maclaurin symmetric mean (MSM) operator is a powerful tool to integrate multiple input arguments, which has the characteristic of considering the interrelationships among the input arguments. In this paper, we extend the traditional MSM operator to the single-valued neutrosophic interval 2-tuple linguistic environment, propose some novel aggregation operators, and develop a novel method to solve multiple attribute group decision making (MAGDM) problems. Firstly, we put forward the concept of single-valued neutrosophic interval 2-tuple linguistic sets (SVN-ITLSs) by combining the definitions of single-valued neutrosophic sets and interval 2-tuple. Secondly, the Maclaurin symmetric mean is extended to the single-valued neutrosophic interval 2-tuple linguistic environment and three new aggregation operators are proposed, such as the single-valued neutrosophic interval 2-tuple linguistic Maclaurin symmetric mean (SVN-ITLMSM) operator, the single-valued neutrosophic interval 2-tuple linguistic weighted average (SVN-ITLWA) operator and the single-valued neutrosophic interval 2-tuple linguistic weighted Maclaurin symmetric mean (SVN-ITLWMSM) operator. Some desirable properties of the proposed SVN-ITLMSM operator are investigated. Thirdly, an approach to solve MAGDM problem is developed based on the proposed operators. Finally, a numerical example is given to illustrate the application and the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In the classical LINear programming technique for Multidimensional Analysis of Preference (LINMAP), the criteria are assumed to be independent, which may cause distorted results. The aim of this paper is to employ the LINMAP to develop an interval-valued intuitionistic fuzzy (IVIF) mathematical programming method for multicriteria group decision making considering not only the importance of criteria and that of their ordered positions but also the interactions among criteria and those among their ordered positions. In the spirit of LINMAP, new group consistency and group inconsistency indices based on cross-entropy and Shapley values are firstly defined by considering the interactions among criteria and among their ordered positions. To simultaneously determine the fuzzy measures on criteria set and on ordered set, a bi-objective IVIF programming model is then constructed by minimizing the inconsistency index and maximizing the consistency index. The proposed IVIF programming model is subsequently solved by transforming it into a multiobjective programming model. Furthermore, some generalizations of the proposed programming model are investigated. Finally, two examples are given to illustrate the application of the proposed method, and its superiority is demonstrated by comparing the performance of the proposed method with that of the existing methods. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute group decision making (MAGDM) problems in which the attributes are dependent and the attribute values take the forms of intuitionistic linguistic numbers and intuitionistic uncertain linguistic numbers, this paper investigates two novel MAGDM methods based on Maclaurin symmetric mean (MSM) aggregation operators. First, the Maclaurin symmetric mean is extended to intuitionistic linguistic environment and two new aggregation operators are developed for aggregating the intuitionistic linguistic information, such as the intuitionistic linguistic Maclaurin symmetric mean (ILMSM) operator and the weighted intuitionistic linguistic Maclaurin symmetric mean (WILMSM) operator. Then, some desirable properties and special cases of these operators are discussed in detail. Furthermore, this paper also develops two new Maclaurin symmetric mean operators for aggregating the intuitionistic uncertain linguistic information, including the intuitionistic uncertain linguistic Maclaurin symmetric mean (IULMSM) operator and the weighted intuitionistic uncertain linguistic Maclaurin symmetric mean (WIULMSM) operator. Based on the WILMSM and WIULMSM operators, two approaches to MAGDM are proposed under intuitionistic linguistic environment and intuitionistic uncertain linguistic environment, respectively. Finally, two practical examples of investment alternative evaluation are given to illustrate the applications of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiple attribute group decision making (MAGDM) problems with 2-tuple linguistic information. Firstly, motivated by the ideas of Choquet integral and Shapley index, we propose three 2-tuple linguistic aggregation operators called Shapley 2-tuple linguistic Choquet averaging operator, Shapley 2-tuple linguistic Choquet geometric operator and generalized Shapley 2-tuple linguistic Choquet averaging operator. Then we discuss some properties of these operators, such as idempotency, monotonicity, boundary and commutativity. Secondly, if the information about the weights of decision makers (DMs) and attributes is incompletely known, we build two models to determine the optimal fuzzy measures on DM set and attribute set, respectively. Furthermore, we develop a new method for multiple attribute group decision making under 2-tuple linguistic environment based on the proposed operators. Finally, we apply the developed MAGDM method to select the most desirable emergency alternative and the validity of the developed method is verified by comparing the evaluation results with those obtained from the existing 2-tuple correlated aggregation operators. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute group decision making (MAGDM) problems in which the assessment values of attributes take the form of interval-valued hesitant uncertain linguistic elements, a novel MAGDM method is proposed in this paper. Firstly, the concept, operational laws and score function of interval-valued hesitant uncertain linguistic elements (IVHULEs) are introduced. Then, based on the operational laws of IVHULEs, some generalized aggregation operators are proposed for aggregating the interval-valued hesitant uncertain linguistic information, including the generalized interval-valued hesitant uncertain linguistic weighted aggregation operators, the generalized interval-valued hesitant uncertain linguistic ordered weighted aggregation operators and the generalized interval-valued hesitant uncertain linguistic hybrid aggregation operators. Furthermore, some desirable properties of these operators and the relationships between them are discussed. Based on the proposed operators, an approach to multiple attribute group decision making with unknown weight information is developed under interval-valued hesitant uncertain linguistic environment. Finally, a numerical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

With respect to multi-attribute group decision-making (MAGDM) problems in which the attribute values take form of intuitionistic trapezoid fuzzy linguistic numbers, some new aggregation operators are proposed, such as intuitionistic trapezoid fuzzy linguistic weighted geometric operator, intuitionistic trapezoid fuzzy linguistic ordered weighted geometric operator, intuitionistic trapezoid fuzzy linguistic hybrid weighted geometric operator, intuitionistic trapezoid fuzzy linguistic generalized weighted averaging operator, intuitionistic trapezoid fuzzy linguistic generalized ordered weighted averaging operator and intuitionistic trapezoid fuzzy linguistic generalized hybrid weighted averaging operator are proposed at first. Then, some desirable properties of these proposed operators are discussed, including monotonicity, idempotency, commutativity and boundedness. Furthermore, based on the proposed operators, some novel methods are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information under different cases. Finally, an illustrative example of emergency response capability evaluation is provided to illustrate the applicability and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

As a risk modeling about fuzzy numbers, R-numbers have successfully extended to multi-criteria decision making (MCDM) methods for the real-life decision making problems involving the risk and uncertainties associated with fuzzy numbers. To obtain more reliable and robust multi-criteria ranking alternatives in these uncertain situations, a hybrid decision making aided framework involving stochastic multiobjective acceptability analysis (SMAA), robust ordinal regression (ROR), and multi-attributive border approximation area comparison (MABAC) is proposed for MCDM problems with risk factors and preference models. Firstly, some novel operations of the R-numbers associated with triangular fuzzy numbers are proposed to explore a broader application scope. Secondly, a novel MABAC method combined with the R-numbers is proposed for MCDM problems which focus on uncertainty and error of triangular fuzzy numbers. Thirdly, a hybrid decision making aided framework which applies SMAA and ROR into the novel MABAC method is proposed for obtaining robust multi-criteria ranking alternatives through two binary relations, and two measures complement each other. Moreover, a Monte Carlo simulation of the framework is performed. Lastly, an application of assessment of wind energy potential and comparative analysis is provided to illustrate the efficiency and superiority of the proposed framework. • A novel MABAC method combined with R-numbers is proposed. • We extend ROR to novel MABAC for the quantitative relation of alternatives. • We extend SMAA to novel MABAC for qualitative relationship of alternatives. • A hybrid decision making aided framework is proposed for robust ranking. • A Monte Carlo simulation of the aided framework is performed. [ABSTRACT FROM AUTHOR]

Dual hesitant fuzzy set (DHFS), which permits the possible membership degrees and non-membership degrees of an element having sets of values in [0,1], is considered as a powerful tool to express uncertain information in the process of multiple attribute group decision making (MAGDM). In this paper, we study the MAGDM problems in which the attribute values take the form of dual hesitant fuzzy elements and the weights of attributes and decision makers take the form of real numbers. Firstly, the normalized Hamming distance of the dual hesitant fuzzy elements is defined. Then, a new method for dealing MAGDM problems under dual hesitant fuzzy environment is proposed on the basis of grey relational analysis (GRA) theory. For the incompletely known and completely unknown information of attribute weight, some optimization models are established to determine the weights of attributes. Finally, a numerical example of investment alternative selection is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

With respect to multiple attribute decision making (MADM) problems in which the attributes are inter-dependent and take the form of dual hesitant fuzzy elements, a new MADM method with dual hesitant fuzzy information is investigated in this paper. Firstly, by using the Choquet integral, some new aggregation operators are developed for aggregating the dual hesitant fuzzy information, such as the dual hesitant fuzzy Choquet ordered average (DHFCOA) operator, the dual hesitant fuzzy Choquet ordered geometric (DHFCOG) operator, the generalized dual hesitant fuzzy Choquet ordered average (GDHFCOA) operator and the generalized dual hesitant fuzzy Choquet ordered geometric (GDHFCOG) operator. Then, some special cases, desirable properties of these operators and the relationships between them are discussed. Furthermore, based on the DHFCOA operator, an approach to MADM is proposed under dual hesitant fuzzy environment. Finally, a numerical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we extend the Hamacher operations to aggregate the dual hesitant fuzzy elements (DHFEs). Firstly, operational rules of DHFEs based on Hamacher t-norm and t-conorm are proposed. Then, we develop some dual hesitant fuzzy Hamacher aggregation operators based on the operational rules of DHFEs, such as dual hesitant fuzzy Hamacher weighted averaging (DHFHWA) operator, dual hesitant fuzzy Hamacher weighted geometric (DHFHWG) operator, dual hesitant fuzzy Hamacher ordered weighted averaging (DHFHOWA) operator, dual hesitant fuzzy Hamacher ordered weighted geometric (DHFHOWG) operator, dual hesitant fuzzy Hamacher hybrid averaging (DHFHHA) operator and dual hesitant fuzzy Hamacher hybrid geometric (DHFHHG) operator are proposed. Some desirable properties of these operators such as idempotency and boundedness are discussed, and some special cases of these operators are analyzed. Furthermore, a method to multiple attribute decision making (MADM) based on the proposed operators is developed. Finally, a practical example is given to illustrate the developed method and a comparison analysis is also conducted, which further demonstrates the practicality and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

A new method is proposed to solve multiple criteria group decision making (MCGDM) problems, in which both the criteria values and criteria weights take the form of linguistic information, and the information about linguistic criteria weights is partly known or completely unknown. Firstly, to get reasonable decision result, instead of assigning the same weight to the decision maker (DM) for all criteria, we propose a method to determine the weight of DM with respect to each criterion under linguistic environment by calculating the similarity degree between individual 2-tuple linguistic evaluation value and the mean given by all decision makers (DMs). Secondly, for the situations where the information about the criteria weights is partly known or completely unknown, we establish optimization models to determine the criteria weights by defining 2-tuple linguistic positive ideal solution (TL-PIS), 2-tuple linguistic right negative ideal solution (TL-RNIS) and 2-tuple linguistic left negative ideal solution (TL-LNIS) of the collective 2-tuple linguistic decision matrix. Thirdly, we propose a new method to solve MCGDM problems with partly known or completely unknown linguistic weight information. Finally, an illustrative example is given to demonstrate the calculation process of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the multi-attribute decision making (MADM) problems under two situations that the attributes are independent and correlative, respectively, in which the attribute values take the form of dual hesitant fuzzy linguistic elements and the weights of attributes take the form of real numbers. Firstly, the concept, operational laws, score function and accuracy function of dual hesitant fuzzy linguistic element (DHFLE) are defined. For the situation that the attributes are independent, some dual hesitant fuzzy linguistic geometric aggregation operators are proposed. Considering that there exists prioritization among the attributes, we propose several dual hesitant fuzzy linguistic prioritized aggregation operators based on the prioritized average (PA) operator. Moreover, some desirable properties and special cases of these operators are investigated in detail. Based on the proposed operators, two novel approaches to MADM with dual hesitant fuzzy linguistic information are proposed. Finally, a numerical example for investment alternative selection is given to illustrate the application of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper investigates multiple attribute decision making (MADM) problems in which the attribute values take the form of interval-valued dual hesitant fuzzy elements (IVDHFEs). Firstly, motivated by the concepts of dual hesitant fuzzy set (DHFS) and interval number, the concept, operational laws and comparison laws of interval-valued dual hesitant fuzzy elements are proposed. Then, based on the operational laws of IVDHFEs, some aggregation operators are developed for aggregating the interval-valued dual hesitant fuzzy information, such as the interval-valued dual hesitant fuzzy weighted aggregation operators, the interval-valued dual hesitant fuzzy ordered weighted aggregation operators, the generalized interval-valued dual hesitant fuzzy weighted aggregation operators, the generalized interval-valued dual hesitant fuzzy ordered weighted aggregation operators and the interval-valued dual hesitant fuzzy hybrid aggregation operators. Furthermore, some desirable properties of these operators and the relationships between them are discussed in detail. Based on the interval-valued dual hesitant fuzzy weighted average (IVDHFWA) operator, an approach to multiple attribute decision making is proposed under interval-valued dual hesitant fuzzy environment. Finally, a numerical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

This paper investigates the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant intuitionistic fuzzy linguistic elements (HIFLEs). Firstly, motivated by the idea of hesitant fuzzy linguistic elements and intuitionistic fuzzy numbers, the concept, operational laws and comparison laws of HIFLEs are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic fuzzy linguistic information, such as hesitant intuitionistic fuzzy linguistic weighted aggregation operators, hesitant intuitionistic fuzzy linguistic ordered weighted aggregation operators and hesitant intuitionistic fuzzy linguistic hybrid aggregation operators. Some desirable properties of these operators and the relationships between them are discussed. Furthermore, the hesitant intuitionistic fuzzy linguistic set is extended to hesitant intuitionistic fuzzy uncertain linguistic set, and some hesitant intuitionistic fuzzy uncertain linguistic aggregation operators are developed. Based on the hesitant intuitionistic fuzzy linguistic weighted average (HIFLWA) operator, an approach to MADM is proposed under hesitant intuitionistic fuzzy linguistic environment. Finally, a practical example is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the multiple attribute decision making (MADM) problems in which the attribute values take the form of trapezoid fuzzy 2-tuples. Firstly, we develop some trapezoid fuzzy 2-tuple linguistic aggregation operators based on the operational laws of trapezoid fuzzy 2-tuples, such as the trapezoid fuzzy 2-tuple weighted geometric (TFTWG) operator, the trapezoid fuzzy 2-tuple ordered weighted geometric (TFTOWG) operator, the generalized trapezoid fuzzy 2-tuple weighted average (GTFTWA) operator and the generalized trapezoid fuzzy 2-tuple ordered weighted average (GTFTOWA) operator. Then, we study some desirable properties of the developed operators, such as idempotency, monotonicity, commutativity and boundedness, and analyze some special cases of these operators. Furthermore, we propose an approach to multiple attribute decision making under trapezoid fuzzy linguistic environment based on the GTFTWA and TFTWG operators. Finally, an illustrative example is given to verify the proposed approach and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

We investigate the multi-attribute group decision making (MAGDM) problems in which the attribute values provided by the decision makers take the form of intuitionistic trapezoid fuzzy linguistic (ITrFL) information considering the uncertainty and inaccuracy of input arguments. Some new power aggregation operators called intuitionistic trapezoid fuzzy linguistic power average (ITrFLPA) operator, intuitionistic trapezoid fuzzy linguistic power weighted average (ITrFLPWA) operator, intuitionistic trapezoid fuzzy linguistic power ordered weighted average (ITrFLPOWA) operator, intuitionistic trapezoid fuzzy linguistic power hybrid weighted average (ITrFLPHWA) operator, intuitionistic trapezoid fuzzy linguistic power geometric (ITrFLPG) operator, intuitionistic trapezoid fuzzy linguistic power weighted geometric (ITrFLPWG) operator, intuitionistic trapezoid fuzzy linguistic power ordered weighted geometric (ITrFLPOWG) operator and intuitionistic trapezoid fuzzy linguistic power hybrid weighted geometric (ITrFLPHWG) operator are proposed. Then, we study some desirable properties of the proposed operators, such as idempotency, commutativity and boundedness. In addition, two novel approaches based on the proposed operators are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information. Finally, a numerical example is provided to verify the feasibility of the proposed approaches. [ABSTRACT FROM AUTHOR]

Abstract: Multiple criteria group decision making (MCGDM) problems have become a very active research field over the last decade. Many practical problems are often characterized by MCGDM. The aim of this paper is to develop a new approach for MCGDM problems with incomplete weight information in linguistic setting based on the projection method. Firstly, to reflect the reality accurately, a method to determine the weights of decision makers in linguistic setting is proposed by calculating the degree of similarity between 2-tuple linguistic decision matrix given by each decision maker and the average 2-tuple linguistic decision matrix. By using the weights of decision makers, all individual 2-tuple linguistic decision matrices are aggregated into a collective one. Then, to determine the weight vector of criteria, we establish a non-linear optimization model based on the basic ideal of the projection method, i.e., the optimal alternative should have the largest projection on the 2-tuple linguistic positive ideal solution (TLPIS). Calculate the 2-tuple linguistic projection of each alternative on the TLPIS and rank all the alternatives according to the 2-tuple linguistic projection value. Finally, an illustrative example is given to demonstrate the calculation process of the proposed method, and the validity is verified by comparing the evaluation results of the proposed method with that of the technique for order preference by similarity to ideal solution (TOPSIS) method. [Copyright &y& Elsevier]

In order to win in the market competition, enterprises have considered sustainable high-quality development (SHQD) as an important goal. However, prior studies on SHQD mainly emphasized theoretical discussions, and few scholars have conducted quantitative data analysis, especially in the state-owned enterprises (SOEs) area. Given this research gap, this paper proposes a novel framework to evaluate and select state-owned enterprise with sustainable high-quality development capacity (SHQDC) in China under linguistic distribution assessment (LDA) environment. This study has been done in four stages. In the first stage we present a detailed evaluation index system for SHQDC. In the second stage, to determine the comprehensive weights of evaluation criteria and sub-criteria, we extend the traditional fuzzy analytic hierarchy process (FAHP) method to determine the subjective weights of criteria and sub-criteria, and propose a novel method to compute the objective weights of criteria and sub-criteria under linguistic distribution assessment environment. In the third stage, we extend the traditional bidirectional projection method to the linguistic distribution environment and further put forward a ranking method to select SOEs with SHQDC, in which the ratings of sub-criteria are assessed in linguistic distribution assessments to reflect the qualitative evaluation of experts' subjective opinions. Finally, we demonstrate the validity of the proposed approach by means of comparing the sustainable high-quality development capacity of three state-owned enterprises in China. [ABSTRACT FROM AUTHOR]

Abstract: A new method is proposed to solve multi-criteria group decision making problems in which both the criteria values and criteria weights take the form of linguistic information based on the traditional idea of VIKOR method. Firstly, the linguistic criteria weights given by all decision makers are transformed into trapezoidal fuzzy numbers, and then aggregated and defuzzified to crisp values. Secondly, the individual linguistic decision matrix given by each decision maker (DM) is transformed into 2-tuple linguistic decision matrix, and then aggregated into collective 2-tuple linguistic decision matrix by 2-tuple linguistic arithmetic mean operation. Thirdly, the 2-tuple linguistic values and are calculated by defining the 2-tuple linguistic positive ideal solution (TL-PIS) and 2-tuple linguistic negative ideal solution (TL-NIS). Furthermore, the compromise solution can be obtained. Finally, a numerical example is used to illustrate the application of the proposed approach, and the method is verified by comparing the evaluation result with that of 2-tuple linguistic TOPSIS (TL-TOPSIS) method. [Copyright &y& Elsevier]

Abstract: Emergency management (EM) is a very important issue with various kinds of emergency events frequently taking place. One of the most important components of EM is to evaluate the emergency response capacity (ERC) of emergency department or emergency alternative. Because of time pressure, lack of experience and data, experts often evaluate the importance and the ratings of qualitative criteria in the form of linguistic variable. This paper presents a hybrid fuzzy method consisting fuzzy AHP and 2-tuple fuzzy linguistic approach to evaluate emergency response capacity. This study has been done in three stages. In the first stage we present a hierarchy of the evaluation index system for emergency response capacity. In the second stage we use fuzzy AHP to analyze the structure of the emergency response capacity evaluation problem. Using linguistic variables, pairwise comparisons for the evaluation criteria and sub-criteria are made to determine the weights of the criteria and sub-criteria. In the third stage, the ratings of sub-criteria are assessed in linguistic values represented by triangular fuzzy numbers to express the qualitative evaluation of experts’ subjective opinions, and the linguistic values are transformed into 2-tuples. Use the 2-tuple linguistic weighted average operator (LWAO) to compute the aggregated ratings of criteria and the overall emergency response capacity (OERC) of the emergency alternative. Finally, we demonstrate the validity and feasibility of the proposed hybrid fuzzy approach by means of comparing the emergency response capacity of three emergency alternatives. [Copyright &y& Elsevier]

Abstract: How to select suitable emergency alternative is critical to emergency management and has attracted much attention for both researchers and practitioners. In the process of evaluating emergency alternative problems, there usually exists incomplete and uncertain information, and the decision makers can not easily express their judgments on the candiates with exact and crisp values. The Dempster–Shafer theory (DST) is well suited for dealing with such problems and can generate comprehensive assessments for different alternatives. In this paper, the DS/AHP method and extended TOPSIS method are incorporated to solve group multi-criteria decision making (GMCDM) problems with incomplete information. The proposed method involves three steps: (1) Identify the focal elements of each decision maker according to the group decision matrix. (2) Construct the group weighted normalized belief interval decision matrix using Dempster’s rule of combination. (3) Propose the Extended TOPSIS approach for group interval data to rank the emergency alternatives. In this method, the positive ideal solution vector is defined as the maximum plausibility of all emergency alternatives with respect to each criterion, and the negative ideal solution vector is defined as the minimum belief of all emergency alternatives with respect to each criterion. An emergency alternative evaluation selection problem is taken as an illustrative example to demonstrate the feasibility and practicability of the proposed methods for group decision making in emergency management. [Copyright &y& Elsevier]

The issue of sustainability has been a prime concern as a continued surging amount of construction and demolition waste (CDW) is being generated while natural resources are consumed and contaminated at an alarming rate. However, CDW utilization involves a range of options based on combinations of different crushing options and manufacture of various recycled products, which is confusing for practitioners to decide the optimal CDW utilization scheme from a comprehensive perspective. To assist decision making among CDW utilization schemes, a heterogeneous multi-criteria evaluation framework is proposed where interval numbers, triangular fuzzy numbers (TFNs) and trapezoidal fuzzy numbers (TrFNs) are used for comprehensive evaluation, enabling experts to present assessment information flexibly based on their preferences, knowledge and nature of different data forms. Firstly, a comprehensive index system is constructed from social, environmental, financial and technical dimensions for the evaluation of CDW utilization schemes. Afterwards, a novel method is proposed to unify heterogeneous evaluation values into rough numbers. Thirdly, to fully reflect both inner and outer dependencies among criteria, the analytic network process (ANP) method is utilized to derive weights of criteria and sub-criteria, before the fuzzy multi-attributive border approximation area comparison (MABAC) method is applied to obtain the final ranking. Finally, a case study of CDW utilization schemes selection problem is illustrated where the scheme of on-site crushing combined with production of recycled bricks and aggregates is selected as the best option with the sum of the distance S k between alternatives and the border approximation areas obtained as [0.0037, 0.0544], and a comparative analysis is conducted to verify its effectiveness and validity of the proposed framework. [ABSTRACT FROM AUTHOR]

Retrofitting energy-inefficient external walls would improve the energy performance of building envelope by utilizing new insulation materials to decrease heat transfer. However, previous researches mainly based on environmental and economic considerations are still partial and could hardly provide a holistic perspective for the optimal selection of external walls retrofit techniques. To address this problem, this paper proposes a novel heterogeneous multi-criteria group decision-making (MCGDM) framework in which the ratings of schemes are described with real numbers and linguistic variables and the weights of criteria are unknown. Firstly, an evaluation index system is established covering criteria of thermal insulation property, technique, durability, and economic efficiency. Secondly, building information modeling (BIM) is utilized to determine multiple retrofit schemes and derive the heat transfer coefficient. Thirdly, after heterogeneous evaluation values are unified, a combined weighting approach is developed based on best worst method (BWM) and the similarity method before fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is applied to rank the alternatives. Fourthly, the applicability of the proposed framework is demonstrated by a case study of the external wall retrofit scheme selection in Beijing, which reveals that extruded polystyrene (XPS) and expanded polystyrene (EPS) insulation schemes are the compromise choices with aggregating index Q k of 0.0032 and 0.0967 respectively, while rock wool insulation scheme is the last option with Q k of 0.7182. The stability of ranking results is proved with the changing weight of maximum group utility, and the effectiveness of the proposed framework is verified by a comparative analysis. This study can facilitate the implementation of building envelope retrofit by providing useful guidance for selection of external wall retrofit schemes. • A heterogeneous MCGDM framework is proposed to assess retrofit schemes. • BIM is integrated with MCDM method for a comprehensive evaluation. • XPS and EPS schemes are the compromise choices for the case study. • A novel method is proposed to convert two data forms to a unified form. • The extended application of proposed framework facilitates urban green retrofit. [ABSTRACT FROM AUTHOR]

Selecting a sustainable municipal solid waste management (MSWM) scenario can reduce greenhouse gas emissions and deal with the energy crisis, effectively. However, traditional decision approaches only rank alternative scenarios but fail to manage them. Implementing effective management for alternative MSWM scenarios can save decision costs and improve efficiency. Thus, this paper aims to construct a novel multi-criteria group decision-making (MCGDM) methodology to manage and rank sustainable scenarios. To evaluate sustainable MSWM scenarios, a comprehensive evaluation index system is constructed from five dimensions including economy, environment, society, technology, and energy. The hesitant fuzzy linguistic term set is employed to articulate evaluation information. Given the importance of experts and the incomplete criteria weight information, an inclusion measure-based approach is proposed to obtain expert weights, and the grey relational analysis linear programming model with incomplete criteria weight information is constructed to determine criteria weights. An inclusion measure-based hesitant fuzzy linguistic multigranulation three-way decisions over two universes approach is developed to manage and rank alternative MSWM scenarios. The feasibility of the proposed methodology is illustrated by a numerical case. Triple sensitivity analysis is performed from the perspectives of decision-makers' risk appetite, expert weight fluctuations, and criteria weight fluctuations. A comparative analysis is implemented to demonstrate the effectiveness and superiority of the proposed methodology. This study provides a novel insight to solve MSWM scenario selection and can extensively be applied to handle other MCGDM problems. • Constructing a comprehensive evaluation index system from multiple dimensions. • Describing evaluation criteria by hesitant fuzzy linguistic term set. • Proposing an inclusion measure-based approach to derive expert weights. • Employing a grey relational analysis linear programming model to determine criteria weights. • Developing an inclusion measure-based multigranulation three-way decisions to manage and rank all alternative scenarios. [ABSTRACT FROM AUTHOR]

Access to and investment in renewable energy are considered as essential factors in sustainable development. Recently, renewable energy sources and assessing their investment risk have attracted much attention, especially for companies willing to invest in the Belt and Road Initiative countries. As the main objective of the present research, investment risk factors of renewable energies in these countries are identified and categorized into five groups as economic, technical, environmental, social, and political using TODIM (Portuguese acronym for Interactive Multi-Criteria Decision Making) method. Then, the identified factors are weighted by the fuzzy-analytic network process (F-ANP) and different renewable energy sources are ranked by COPRAS, MABAC, and GRA methods under uncertainty conditions. Finally, the sensitivity analysis of investment decision making was carried out with the emphasis being placed on the tradability aspect of renewable energy projects. The results show that wind energy has a lower investment risk besides the higher economic justification, followed by hydropower. The results of this research are useful for policymakers, investors, and companies working in the field of renewable energies to assist them in the assessment of their investment projects and the expansion of their international markets. Image 1 • Investment risk analysis of the Belt and Road Initiative countries by the TODIM. • Weighting the evaluation criteria by Fuzzy-ANP. • Renewable energy sources ranking by COPRAS, MABAC, and GRA methods. • Sensitivity analyzing the RE investment decisions based on the tradability factor. [ABSTRACT FROM AUTHOR]

The waste-to-energy (WTE) project can handle the expanding volume of municipal solid waste (MSW) and promote the development of the circular economy, effectively. To achieve sustainable MSW management, it is pivotal to select a promising WTE incineration plant site. Thus, this paper aims to propose a novel methodology for selecting the optimal WTE incineration plant site. A sustainable evaluation index system is constructed from the environment, economy, society, risk, and energy aspects. Evaluation criteria are articulated by mathematical models and hesitant fuzzy linguistic term set, respectively. Given interactional relations among criteria and computation efficiency, HFL-BWM-ANP (hesitant fuzzy linguistic Best-Worst method-Analytic Network Process) is proposed to obtain criteria weights. The double parameters TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach is employed to rank alternative sites. The feasibility of the proposed methodology is illustrated by a numerical case. Triple sensitivity analysis and comparative analysis are performed to demonstrate the robustness, effectiveness, and superiority of the proposed methodology. Some managerial insights are provided from multiple dimensions for investors and the government to implement the WTE incineration plant project. Image 1 • Constructing a sustainable evaluation index system from multiple dimensions. • Articulating evaluation criteria by mathematical models and hesitant fuzzy linguistic term set, respectively. • Proposing a weighting model to improve efficiency and handle correlations among criteria. • Introducing the double parameters TOPSIS method to rank WTE incineration plant sites. • Providing managerial insights for investors and the government to manage WTE incineration plants. [ABSTRACT FROM AUTHOR]

• A framework is proposed to comprehensively assess multiple construction equipment. • Trust degrees are considered to obtain weights of experts in social networks by SNA. • 2DULVs are used to express subjective values involving assessment of reliability. • 2DULPGWA operator is used to aggregate subjective value and reduce information loss. • An evaluation index system is developed to assess loaders' comprehensive performance. Selecting the proper construction equipment is a challenging task owing to a wide range of available types as well as a host of criteria to be considered during decision making. To deal with this, a heterogeneous group decision-making framework to evaluate multiple purchasing choices of construction equipment is proposed with two data forms, i.e., 2-dimension uncertain linguistic variables (2DULVs) and real numbers. Firstly, a novel way to derive weights of experts by social network analysis (SNA) is applied considering trust degrees among experts in a social trust network. Secondly, after evaluation index system is established, 2DULVs that include both the linguistic evaluations on alternatives and decision makers' appraisals on the given evaluation results are applied to represent subjective fuzzy evaluation information, while real numbers are used to represent quantitative values. Thirdly, 2-dimension uncertain linguistic power generalized weighted aggregation (2DULPGWA) operator is applied to aggregate evaluation values among experts. Fourthly, analytic hierarchy process (AHP) and entropy method are utilized to derive combined weights of sub-criteria before the rank can be obtained by the evaluation based on distance from average solution (EDAS) method. Finally, a case study to evaluate multiple choices of loaders is proposed and a comparative analysis is conducted to prove the effectiveness of the proposed framework. This study provides a meaningful guidance for the optimal selection among various types of construction equipment. [ABSTRACT FROM AUTHOR]

Due to the continuous cost reduction and technological innovation, electronic products are easily accessible to individuals and become omnipresent in our day-to-day lives. For electronics manufacturing enterprises, the pressure to maintain a competitive edge and the urgency to implement sustainable development makes the optimal selection of green supplier a necessity during operations. Although some studies have given some methods for green supplier selection, the consensus problem has not been sufficiently studied in the existing methods. In order to solve this problem, we propose a group consensus decision making framework to help choosing the best green supplier for electronics manufacturing. Firstly, decision makers' preferences between the alternatives considered with respect to each criterion are elicited by the paired comparison method, and expressed as probabilistic linguistic preference relations. Secondly, a new consistency measure is defined and a convergent algorithm is described to aid the consistency improvement process in a given probabilistic linguistic preference relation. The algorithm adopts a local revision strategy and can be easily interpreted. Further, for the consensus model, in each round of this dynamic and interactive model, the most incompatible expert is asked to revise his/her judgment according to judgment feedback mechanism. If the expert rejects the suggestion, his/her weight of importance will be decreased based on the weighting feedback mechanism. Finally, a case study of selecting green supplier is provided to illustrate the application of the proposed group consensus decision making framework. Image 1 • A consistency convergent algorithm is proposed to elicit high quality probabilistic linguistic preference relations. • A consensus convergent algorithm is developed to obtain unanimous green supplier evaluation information. • A consensus reaching-based framework is put forward to aid the green supplier selection. • Probabilistic linguistic preference relation are used to express decision makers' preferences. [ABSTRACT FROM AUTHOR]

In the multi-attribute decision-making (MADM) problems, decision makers refer to the extreme attribute values in general when evaluating the alternatives. However, in the real world, the ideal solution may lie in somewhere between the extreme values. The recently proposed reference ideal method (RIM) is able to solve the problem rightly. This study aims at developing a novel MADM framework combining best–worst method (BWM), maximizing deviation method (MDM), and RIM under Z-number environment. In this framework, Z-number is used to depict the inherent uncertainty and reliability of information in the decision makers' judgments. And BWM and MDM are combined to determine the comprehensive attribute weights, in which BWM is utilized to obtain the subjective weights, while MDM is utilized to obtain the objective weights. In addition, Z-RIM is proposed by extending the traditional RIM under Z-number environment, which is employed for ranking the alternatives. An illustrative example of cloud service selection problem is implemented to illustrate the proposed framework. By comparison analysis, we demonstrate that Z-RIM can not only avoid rank reversal problem, but also generate reasonable results during the MADM processes. [ABSTRACT FROM AUTHOR]

Efficient and trustable food delivery systems have a great impact on our daily life. Considering environmental protection, Electric Cold-chain Vehicle (ECV) has been adopted to support the food delivery system in urban area. However, the drivers of ECV has the motivation to power off the refrigerator for saving electricity, which would lead to the food safety issue. Driven by this, we proposed a novel blockchain-based Electric Cold-chain Delivery System (BECDS) and concentrated on the EV charging and scheduling problem in the distribution network. In terms of methodology innovation, the Dynamic charging and service schedule model (DCSSM) is proposed based on the multi-agent-based simulation. Meanwhile, Internet of Things (IOT) devices are used to monitor the environment data of food, which would be recorded in the blockchain. Furthermore, this paper carries out numerical experiments to verify the feasibility of this system via realistic data. Interestingly, the result shows that the new cold-chain delivery system could serve retailers more efficiently with zero emissions. Hence, this paper could broaden and defined a promising green and digital urban food delivery prototype in the future. • This paper proposed an intelligent urban food delivery system supported by electric vehicles and blockchain. • Detailed service and charging simulation model is constructed considering the dynamic green delivery scenarios. • Elaborately technological framework is designed to make the intelligent blockchain-based system more applicable. • The proposed novel green delivery system is verified by the realistic business data in Shanghai, China. [ABSTRACT FROM AUTHOR]

Under the restriction of carbon neutral and carbon peak, the development of green building has become the strategic demand of most countries in the world. Despite the rapid development of green building in China, there are still some problems, such as insufficient market development force under the government's leadership, emphasizing design and neglecting operation. In order to realize high-quality synergistic development of green building market, this paper constructs a new synergistic development framework of green building market, establishes a tripartite evolutionary game model including local governments, developers and consumers, uses the analysis tool of evolutionary game theory and synergistic theory to explore the unilateral ESS and the system ESS of green building market. In order to verify the model, this paper adopts a case study method, takes a residential building project in Tianjin, China which has awarded a three-star mark in green building design evaluation as an example for numerical simulation, discusses the influence of government guidance on the system evolution trajectory, demonstrates the interactive process of stakeholders' behavior, and finds out the key factors affecting the system equilibrium strategy. The result shows that (1) the means of government guidance will affect the speed and result of system evolution; (2) the strategy of stakeholders depends on the comparison of costs and benefits; (3) the probability of ideal events is positively correlated with the economic benefits and negatively correlated with incremental cost of green building. This study can provide theoretical guidance for local governments, developers and consumers to make scientific decisions, and provide practical enlightenment for government to play a more active role in green building market. [ABSTRACT FROM AUTHOR]

Cross-border transactions have been more and more popular around the world. However, the current cross-border transactions still have risks and challenges, e.g., differences in regulation policies and unbalanced profits of banks. To address this critical issue, we construct a new framework for the transaction system with the support of blockchain technology. In this paper, we propose a new consortium blockchain system, namely asymmetric consortium blockchain (ACB), to ensure the implementation of cross-border transactions. Different from traditional consortium blockchain, the new blockchain system could support the supernode to regulate all the transactions timely. Furthermore, the new smart contract is designed to lower the opportunity loss for each node and make the profits allocation system fairer. In the end, the numerical experiments were carried out based on the transactions of Shenzhen and Hong Kong. The results show that the proposed ACB system is efficient to make the profit allocation fairer for the participants and keep intelligent for the new cross-border transaction system. [ABSTRACT FROM AUTHOR]

With the concerns of environment protection, electric vehicle (EV) is regarded as a promising transportation tool for green cities project. Since the amount of EV is rising shapely, the EV charging demands is also rapidly generated. However, seeking suitable charging facilities is not easy for EV users, new energy companies run charging station separately for self-interests, and charging pile information is not transparent for drivers. This dilemma is not solved until the merging of blockchain technology. In this paper, a novel EV charging system is proposed for the cooperation of new energy companies and providing convenient charging services for users. In this system, charging information is managed and recorded by the company alliance based on consortium blockchain, which is tamper-resistant and multi-centralized. Meanwhile, a new smart contract is designed to balance the allocation of company' charging users, so that the profits of different new energy companies could be fairer. To equilibrate the interest of companies and EV users, a Bio-Objective Mixed-Integer Programming model (BOMILP) is proposed as the mathematical logic of smart contracts. Furthermore, we proposed a new algorithm named Limited Neighborhood Search with Memory (LNSM) to support the implementation of smart contracts, which could make the smart contract running faster and has a better performance. At last, the proposed EV charging system and the smart contract are validated through a real case study with the EV charging data in Beijing, China. [ABSTRACT FROM AUTHOR]

With the sustainable development of cities, green transportation is regarded as a critical approach to mitigate air pollution and greenhouse gas emissions. Driven by this, Electric vehicles (EV) have been strongly advocated by the government for their zero-emission merit. However, the promotion of EV is not smoothly caused by inconvenient charging issues. For the high construction cost and land scarcity, current public charging stations could not meet the booming charging demands and worry the potential EV users. To address the problem, this paper proposed a peer-to-peer (P2P) private charging pile sharing system supported by blockchain technology. In this system, the charging records of EV users could be packaged and uploaded into the blockchain, which is immutable and tamper-resistant. The detailed blockchain hierarchy is also designed to make this system more practical. Meanwhile, the Multi-Agent-Based (MAB) model is adopted to evaluate the performance of this sharing system. In this model, different participants' behaviors are fully considered and calculated. Furthermore, several numerical experiments are conducted to unveil the inner business relationships between charing demanders and pile suppliers. Lastly, the proposed private pile sharing system is validated by the realistic data of the Lujiazui business circle in Shanghai, China. [Display omitted] • We proposed a novel P2P EV pile sharing system supported by blockchain. • Multi-agent modeling is adopted to evaluate this decentralized sharing system. • The practical architecture and hierarchy are well designed for this system. • The proposed framework is validated by the real data set of Shanghai, China. [ABSTRACT FROM AUTHOR]