A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP

2018

Applied Sciences

Abstract:With the challenge of transportation environment, a large amount of attention is paid to sustainable mobility worldwide, thus bringing the problem of the evaluation of sustainable transport solutions. In this paper, a modified method based on analytical hierarchy process (AHP) and Dempster-Shafer evidence theory (D-S theory) is proposed for evaluating the impact of transport measures on city sustainability. AHP is adapted to determine the weight of sustainability criteria while D-S theory is used for data fusion of the sustainability assessment. A Transport Sustainability Index (TSI) is presented as a primary measure to determine whether transport solutions have a positive impact on city sustainability. A case study of car-sharing is illustrated to show the efficiency of our proposed method. Our modified method has two desirable properties. One is that the BPA is generated with a new modification framework of evaluation levels, which can flexibly manage uncertain information. The other is that the modified method has excellent performance in sensitivity analysis.

Section: Analytic Hierarchy Processmentioning

confidence: 99%

A Modified Method for Evaluating Sustainable Transport Solutions Based on AHP and Dempster–Shafer Evidence Theory

Chen

2018

Applied Sciences

“…In this section, some preliminaries are briefly introduced. In real applications, how to deal with uncertainty in decision making is still an open issue . Many uncertainty information processing models based on the relative math tools, such as fuzzy sets, D numbers, and evidence theory, are presented and adopted in practical engineering.…”

Section: Preliminariesmentioning

confidence: 99%

“…In real applications, how to deal with uncertainty in decision making is still an open issue. [11][12][13][14][15] Many uncertainty information processing models based on the relative math tools, such as fuzzy sets, 16,17 D numbers, [18][19][20] and evidence theory, [21][22][23] are presented and adopted in practical engineering. Among these models, Z numbers is efficient to represent the reliability of uncertain information and can be defined as follows.…”

Section: Preliminariesmentioning

confidence: 99%

Generating Z-number based on OWA weights using maximum entropy

Kang

Hewage

et al. 2018

Int. J. Intell. Syst.

Self Cite

In the application of Z‐number, how to generate Z‐number is a significant and open issue. In this paper, we proposed a method of generating Z‐number based on the OWA weights using maximum entropy considering the attitude (preference) of the decision maker. Some numerical examples are used to illustrate the effectiveness of the proposed method. Results show that the attitude (preference) of the decision maker can give an optimal possibility distribution of the reliability for Z‐number using maximum entropy.

“…Many math tools, such as AHP [37][38][39][40], fuzzy sets [41][42][43], D numbers [44][45][46][47], evidential reasoning [30,[48][49][50][51], and rough sets [52], are adopted with wide applications. In this section, the main concepts about the Dempster-Shafer (D-S) evidence theory are reviewed.…”

Section: Dempster-shafer Theory Of Evidencementioning

confidence: 99%

Evidential Model Validation under Epistemic Uncertainty

Mathematical Problems in Engineering

2018

Self Cite

This paper proposes evidence theory based methods to both quantify the epistemic uncertainty and validate computational model. Three types of epistemic uncertainty concerning input model data, that is, sparse points, intervals, and probability distributions with uncertain parameters, are considered. Through the proposed methods, the given data will be described as corresponding probability distributions for uncertainty propagation in the computational model, thus, for the model validation. The proposed evidential model validation method is inspired by the idea of Bayesian hypothesis testing and Bayes factor, which compares the model predictions with the observed experimental data so as to assess the predictive capability of the model and help the decision making of model acceptance. Developed by the idea of Bayes factor, the frame of discernment of Dempster-Shafer evidence theory is constituted and the basic probability assignment (BPA) is determined. Because the proposed validation method is evidence based, the robustness of the result can be guaranteed, and the most evidence-supported hypothesis about the model testing will be favored by the BPA. The validity of proposed methods is illustrated through a numerical example.