A VIKOR-based approach for assessing the service performance of electric vehicle sharing programs: A case study in Beijing

Xu, Fangqiu; Liu, Jicheng; Lin, Shuaishuai; Yuan, Jinsha

doi:10.1016/j.jclepro.2017.01.162

Cited by 75 publications

(34 citation statements)

References 34 publications

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“…The VIKOR method overcomes this drawback and determines a compromise solution that is closest to the ideal. These comparative findings were discussed in several studies, such as those of Opricovic, Xu et al and Valipour Parkouhi and Safaei Ghadikolaei . These studies showed that the VIKOR method is an effective MCDM method.…”

Section: Introductionmentioning

confidence: 80%

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Private‐sector partner selection for public‐private partnership projects of electric vehicle charging infrastructure

Zhang

Zhao

Kan³

2019

Energy Science & Engineering

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Public‐private partnership (PPP) models, which can mitigate the deflection of charging facilities, have been introduced for electric vehicle charging infrastructure (EVCI) projects. Private‐sector partner selection is a significant step to ensure the success of EVCI‐PPP projects, but it has been rarely studied. This paper therefore identifies selection criteria for private partners in EVCI‐PPP projects and assesses the alternatives using an extended multicriteria operation and compromise solution (VIKOR) method. A partner selection indicator system is established through three development processes, and the factors are categorized into five factor packages: basic ability, management ability, performance of previous performance and credit performance, performance of projects, and sustainable development. These factors include 22 subcriteria. An extended VIKOR‐based method incorporating an intuitionistic fuzzy set is developed to select an optimal private partner. A case study is used to verify the effectiveness and rationalization of the proposed approach. Three potential candidates, P1, P2, P3, are evaluated and ranked according to their evaluation scores, and the results show that P1 is the best partner solution. Relevant charging infrastructure project experience, technical level in charging facilities, and financing plan are the top three criteria for choosing appropriate partners for EVCI‐PPP projects. This study provides a comprehensive evaluation framework for the government to select suitable private‐sector partners to accelerate the sustainable development of charging facilities.

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Section: Introductionmentioning

confidence: 80%

“…In this section, a sensitivity analysis of all criteria is conducted to verify the robustness of the extended VIKOR method . The sensitivity analysis includes a perturbation method, in which the values of alternatives are recalculated, and the order of alternatives is changed when criteria scores change somewhat.…”

Section: Analysis and Findingsmentioning

confidence: 99%

Private‐sector partner selection for public‐private partnership projects of electric vehicle charging infrastructure

Zhang

Zhao

Kan³

2019

Energy Science & Engineering

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“…(2) To dispose the improper ways to determine the weights of TMs with single preference, the proposed QFD model takes the subjective and objective weights into considerations. Since order relation analysis (G1) method [18] and maximum consensus (MC) method [19] are practical means to identify the subjective and objective weights, separately. Further, MC method is improved due to the issue that it merely thinks over the positive ideal point.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus, the G1 method was proposed by Ruan and Yang [46] as a succinct method to get the subjective weights. Due to G1 method's characteristics, it was applied by Xu, Liu [18] to identify criteria weight vector. In this paper, we utilize G1 method to figure out the weights of TMs subjectively.…”

Section: Determining the Subjective Weights Of Tmsmentioning

confidence: 99%

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

Song

Wang

2020

Mathematics

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Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.

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“…Among them, the VIKOR method was proposed for multi objective optimization of complex problems, and is focused on ranking and selecting from among several alternatives in the face of conflicting criteria [33]. Xu et al [34] proposed a VIKOR-based approach to assess the service performance of electric vehicle sharing programs. In terms of site selection, the VIKOR method was applied to deal with the selection of a suitable disposal site for municipal solid waste [14,35] and a dam [36].…”

Section: Literature Reviewmentioning

confidence: 99%

A Decision Framework for Electric Vehicle Charging Station Site Selection for Residential Communities under an Intuitionistic Fuzzy Environment: A Case of Beijing

Xie

et al. 2017

Energies

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Electric vehicle charging station (EVCS) site selection occupies a prominent position in the development of the electric community to solve the hard problem of Electric Vehicle (EV) charging. However, two critical issues have not been solved by the existing research. Firstly, the scope of EVCS site selection only considers the whole city, which deviates from the actual situation. Secondly, the uncertainty and hesitation of decision information is not well expressed. To handle the above problems, this paper builds a comprehensive EVCS site selection decision framework for Residential Communities (EVCSRC) with triangular intuitionistic fuzzy numbers (TIFNs). First of all, the distinctive index system of EVCSRC site selection factors including economy, social, environment, planning and feature portrait of residential communities is established. Then, the TIFNs is utilized for decision makers (DMs) to express the indeterminate information. Furthermore, a fuzzy Vlsekriterijumska Optimizacija I Kompromisno Resenje (Fuzzy-VIKOR) approach is utilized to rank the alternative EVCSRC sites. Finally, a case of Beijing is studied to demonstrate the validity of the proposed site selection framework. The result shows the EVCSRC site located at Sijiqing community in Haidian district should be selected as the optimal site. This paper presents a feasible and easy-to-use decision-making framework for investors.

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A VIKOR-based approach for assessing the service performance of electric vehicle sharing programs: A case study in Beijing

Cited by 75 publications

References 34 publications

Private‐sector partner selection for public‐private partnership projects of electric vehicle charging infrastructure

Private‐sector partner selection for public‐private partnership projects of electric vehicle charging infrastructure

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

A Decision Framework for Electric Vehicle Charging Station Site Selection for Residential Communities under an Intuitionistic Fuzzy Environment: A Case of Beijing

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