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According to the requirement of energy sustainable development strategy in Jilin province, this paper evaluates the performance of wind power coupling compressed air energy storage projects for a wind farm in Jilin from the perspective of sustainability. Firstly, a sustainable criteria system is established from economic, social and ecological dimensions, and 10 secondary criteria are given. Secondly, to fully express the hesitancy and fuzziness of experts, linguistic fuzzy hesitant sets (LFHSs) are used to describe the subjective evaluation information. And then, the cloud model is developed to deal with the randomness and fuzziness of LFHS. Thirdly, a multi criteria decision-making model based on improved Choquet fuzzy integral and deviation degree is proposed for a multi criteria evaluation problem with initial data in the form of crisp values, interval numbers and linguistic fuzzy hesitant sets. The deviation degree can deal with multi-source heterogeneous data and Choquet fuzzy integral improved with Mobius transformation can eliminate the overlap information between criteria. Finally, the case study in Jilin is given to illustrate the effective of the proposed evaluation criteria and technique. From the results, the project 4: wind power coupling compressed air energy storage system with meshing switch is the most suitable alternative for the wand farm, followed by the project of wind power coupling compressed air energy storage system with variable configuration. Moreover, the sensitivity analysis reveals that the project 4 always occupies its top ranking when its weight is floating within a certain range. At last, some policy implications to promote wind power industry are given for the government. • The sustainability evaluation criteria system for wind power project is presented. • A MCDM method based on Choquet fuzzy integral and Mobius transformation is proposed. • Linguistic fuzzy hesitant sets are used to present subjective evaluation information. • The proposed model can deal with multi-source heterogeneous data. [ABSTRACT FROM AUTHOR]

Biomass energy has extensive application foreground in power generation because of its economic and social benefits. Aiming at selecting the best biomass fuel procurement and storage modes in Jilin province, this paper proposes an evaluation model with linguistic hesitant fuzzy sets (LHFSs), which is good at expressing the hesitancy, inconsistency and uncertainty of subjective evaluation information. Based on cloud model and three entropy principle, the transformation between linguistic hesitant fuzzy sets and comprehensive cloud model is realized. In order to eliminate interdependency among criterion, a new Choquet integral aggregation operator based on the Sigmoid function is proposed. According to the expectation values, the ranking result of aggregated LHFSs is obtained. At last, an illustrative example of modes evaluation in Jilin province is taken in the present study to make the proposed method comprehensible. The result shows that mode 3: farmer + middleman + third-party logistics + power plant, is the most reasonable mode for Jilin biomass energy development. From the perspective of supply chain, middlemen and third party logistics can reduce the procurement and transportation cost in the supply chain, which are two bigger influential factors of fuel cost. Middlemen are not only a bridge between plants and farmers, but also the operator in the supply chain. Through the analysis of the result, suggestions from the perspective of power plants and the government are given. • Linguistic hesitant fuzzy sets are used for evaluating biomass power generation fuel procurement and storage modes. • A multi-criteria decision-making method based on cloud model and Choquet integral is proposed. • A new linguistic hesitant fuzzy aggregation operator based on Choquet integral and the Sigmoid function is presented. • "farmer, middleman, third-party logistics and power plant" is the best mode for Jilin biomass power development. [ABSTRACT FROM AUTHOR]

The distributed energy system (DES) has been regarded as a socio-technical innovation that can improve energy efficiency and reduce carbon emission. Based on the construction and planning of a DES project in Henan Province, this paper aims to develop a comprehensive decision-making framework for selecting the most appropriate DES composition schemes with multi-source heterogeneous data. Thus, a new multi-criteria decision-making method based on fuzzy preference relations and improved Choquet integral is generated. Firstly, an evaluation criteria system is established from economic, technical, environmental and social dimensions, and 10 secondary criteria are presented. Secondly, based on the interval fuzzy preference relations of criteria given by experts, the iteration of weights of criteria is continued until the group consistency degree reaches the threshold. Thirdly, the deviation degree is used to transform the initial data, which include crisp values, interval numbers and linguistic terms to isomorphism data. Thereafter, the fuzzy measures are calculated using Mobius transformation coefficients and the final scores of the alternatives are obtained by means of Choquet integral, which can eliminate the overlap information between criteria. Finally, a real case is given to illustrate the effectiveness of the proposed evaluation criteria and technique. The result shows the multi energy complementary system as the most appropriate alternative for the project, followed by the solar-air source heat pump system, fuel cell system, natural gas system, internal combustion engine system and traditional system. Conclusively, the discussion, comparative analysis and some policy implications to promote the development of distributed energy industry are given. This study not only can assist stakeholders to obtain greater benefits of the DES, but also can serve as a reference for the government towards the development of more robust regulations and policies. • Six different distributed energy system (DES) composition schemes are analyzed. • The fuzzy preference relations are developed with the requirement of consistency degree. • A new decision-making method with multi-source heterogeneous data is proposed. [ABSTRACT FROM AUTHOR]

The rapid development of information and communication technologies has created more opportunities for the channel innovation in residential curbside collection and the technical revolution of material recovery facilities. In waste management, single stream allows the households to bundle the recyclable waste, and dual stream requires the households to separate the recyclable waste individually. However, the sustainable development of the environment has led the government to focus on the transition between two waste recycling systems. In this study, we establish an analytical framework of the sequential game to study the sustainable evolution from single stream to dual stream and from dual stream to single stream. When the households are heterogeneous about the recyclable waste, there is a duopoly price competition in waste management, and two waste recycling systems can sequentially adopt the neutral pricing, penetration pricing and skim pricing strategy. Numerical experiments discuss the impacts of collecting costs and bundling discounts on the sustainable evolution. No matter what the evolution sequence is, two waste recycling systems can set a full or partial bundling discount policy to maximize the profit. [ABSTRACT FROM AUTHOR]

As the world's largest energy production and demand country, China's energy security is a hot issue concerned by the whole society. Most existing research focused on China's energy security performance from the point of view of the country. But, as a huge geographical country, provinces energy security performance varies hugely in different regions. So, this paper aims at evaluating Chinese provinces energy security, analyzing reasons and providing policy implications. Firstly, a comprehensive evaluation criteria system, including four dimensions: energy supply, energy using, energy economy and energy environment, is proposed. The criteria consist of 14 indicators. Secondly, Mahalanobis-Taguchi Gram-Schmidt is presented to obtain criteria weights, which not only considers subjective and objective information, but also eliminates the overlap information in criteria. Thirdly, considering that TOPSIS method ignores the correlation between the two distances (alternatives to ideal and to negative ideal), an improved TOPSIS model with set pair analysis is proposed to assess the China's regional energy security performance from 2013 to 2017. From the results, 30 provinces' energy security performance improves in general, but there is still a huge gap among different regions. The north reaches of yellow river and northwest regions are the most energy-secure, while the northeast and central regions are least energy-secure. SHAANXI, INNERMONGOLIA and SHANXI are always top three in the ranking, while the energy security performance of NINGXIA is the lowest. Unlabelled Image • A comprehensive energy security evaluation criteria system which consists of 14 indicators is presented. • To eliminate the overlap information between criteria, Mahalanobis-Taguchi Gram-Schmidt is used to obtain weights of criteria. • A multi criteria decision making method based on set pair analysis and TOPSIS is proposed to evaluate energy security performance. • From 2013 to 2017, Chinese provinces energy security performance improve in general, but there is still a huge gap among different regions. [ABSTRACT FROM AUTHOR]

Abstract: Quality function deployment (QFD) is a planning and problem-solving methodology that is widely used for translating customer requirements (CRs) into engineering characteristics (ECs) of a product. Acquiring ECs in product planning house of quality (PPHOQ) is a crucial step of QFD methodology. In previous studies, methods for acquiring ECs are qualitative and subjective. In this paper, a novel quantitative methodology for acquiring ECs in PPHOQ is presented. In the proposed methodology, a hierarchical framework for generating the refined set of EC candidates from the EC candidates obtained by brainstorming is established. A concept of a general relationship between a CR and an EC is introduced, and then a novel approach for identifying the general relationship measures with the help of intelligent characteristics of rough set is proposed. Another concept of the intension threshold of the general relationship corresponding to a CR is introduced, and then a set-operation-based method of acquiring ECs used in PPHOQ is presented. An example of a two-cylinder washing machine is used to demonstrate the proposed methodology. [Copyright &y& Elsevier]

Abstract: Owing to the typical vagueness or imprecision of customer requirements (CRs) in product planning house of quality (PPHOQ), determining the final importance of CRs is very difficult. Combining rough set theory, Kano’s model, analytical hierarchy process (AHP), and scale method, an integrated method is proposed to obtain the final importance of CRs in PPHOQ. Firstly, by using relative reduction and relative core in rough set theory, a decision system is built to acquire CRs in PPHOQ. Secondly, based on relative positive field in rough set, the decision system is simplified and its corresponding new decision system is established to determine the fundamental importance ratings of CRs. Thirdly, by integrating scale method into AHP approach, calculating formulas of the importance rating of achieving the improvement ratio of satisfaction estimation of a CR are developed. Next, for every CR, based on a combination of its fundamental importance rating, the importance rating of achieving the improvement ratio of its satisfaction estimation, and “its sales point”, its final importance rating is determined. Finally, a case study is provided to illustrate the effectiveness of the presented method. [Copyright &y& Elsevier]

The integrated energy system (IES) has been regarded as a promising energy supply solution due to its high efficiency and low emissions. However, various IES composition schemes exhibit different performance, and decision-makers or stakeholders have experienced difficulty in selecting the most appropriate alternative. This paper aims to develop a multi-criteria decision-making method for a selection problem involving integrated energy system composition schemes in Zhejiang Province, China. As existing research has neglected the interaction between criteria and ignored the subjective risk attitude, this paper proposes a new method based on modified fuzzy integral and prospect theory. First, the criteria's weights are calculated by the Mahalanobis-Taguchi Gram-Schmidt method; the λ fuzzy measures of these criteria are then calculated based on the φs transformation function and weights. This approach not only considers both subjective and objective information, but also eliminates overlapping information between criteria. Second, based on the grey correlation degree and the prospect theory, a prospect decision matrix is obtained that considers decision-makers' subjective risk attitudes. Finally, the alternatives are scored using a fuzzy integral. The results reveal that a complimentary solar and wind based system is the preferred scheme in project construction. Further, comparison and sensitivity analyses verify the proposed model's validity and feasibility, and some suggestions are given to further develop the IES. • Different integrated energy systems exhibit different performance results. • Multi-criteria decision-making is used in selecting integrated energy systems. • The case study involves an industrial park in Zhejiang Province, China. • The Mahalanobis-Taguchi Gram-Schmidt method is used to calculate criterion weights. • This approach considers subjective and objective information without overlaps. [ABSTRACT FROM AUTHOR]

• A new industry-oriented physical safety evaluation index system was created for wearable exoskeleton human-robot collaboration using literature analysis, group decision-making, and the Delphi method. • The new index system improved the comprehensiveness of the existing evaluation index system for wearable exoskeleton human-robot collaboration. An industrial exoskeleton combination safety evaluation model was established to address both the physical safety of industrial exoskeleton human-robot collaboration and the perceived safety of human operators. The new model made the industrial exoskeleton evaluation more comprehensive and systematic, and it has the potential to be applied across different human-robot collaboration scenarios. Wearable exoskeletons are a type of collaborative robots that are widely used in human–robot collaboration, and their safety in the collaboration process has received significant attention. An industrial exoskeleton was the research object of this study. First, the influencing factors found in the relevant literature were analyzed and summarized. Subsequently, a group decision-making method was used to formulate preliminarily evaluation indicators. These indicators were then evaluated using the Delphi method. Based on the finalized evaluation indices, a physical safety evaluation index system for industrial exoskeleton human–robot collaboration was constructed, and an evaluation index model was established to evaluate the physical safety. Simultaneously, a questionnaire on the perceived safety was used to evaluate the perceptions of human operators on the safety of industrial exoskeleton human–robot collaboration. These two types of safety, the physical and perceived safety, were combined in an industrial exoskeleton human–robot collaboration safety evaluation. Three different industrial exoskeletons were used in the case study for this research. Their safety was evaluated using the model proposed in this study, which enabled human operators to quickly and effectively select an industrial exoskeleton through comparative analysis. [ABSTRACT FROM AUTHOR]

The ridesourcing service has taken a large portion of the taxi market in the past few years. Many studies have explored the influencing factors of traditional taxi and ridesourcing demand in different areas of the city. Few studies investigated the market share of ridesourcing in different regions of the city. Understanding the spatial distribution of the market share of ridesourcing service and the factors that determine this distribution could help government agencies understand the role that each type of service plays in the transportation system and evaluate the effect of different public policies on the two types of services. This paper studies this topic by constructing a panel fractional regression model based on the taxi trip data of New York City in 2017. Results show that the market share of the traditional taxi is declining while that of ridesourcing service is increasing. The market share of ridesourcing services is higher in remote areas, areas with low population density, low density of transportation facilities, low household income, and high proportion of young residents. It indicates that ridesourcing service could provide more equitable service by better serving the underserved areas while traditional taxi caters more to the high-demand areas. • We explore built environment factors influencing market share of ridesourcing (RS). • A panel fractional regression model is used to analyze taxi trip data of NYC. • Remote areas, high ratio of low income and young residents are positively related. • Density of population, bus stop, road, and mixed land use are negatively related. • Results could help us understand the interaction of RS and traditional taxi. [ABSTRACT FROM AUTHOR]