scholarly journals Hybrid Predictive Decision-Making Approach to Emission Reduction Policies for Sustainable Energy Industry

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2220
Author(s):  
Chao Zhou ◽  
Dongyu Liu ◽  
Pengfei Zhou ◽  
Jie Luo ◽  
Serhat Yuksel ◽  
...  

Carbon emissions are a prominent issue for sustainable energy production and management. Energy policies under the growing competitive environment could change the priorities of emission reduction and investment decisions. This paper aims to forecast carbon emissions from China and to rank the importance of carbon emissions with interval type 2 (IT2) fuzzy sets (FS) for sustainable energy investments. For this purpose, the quadratic model is applied to measuring emission trends and the Qualitative Flexible Multiple Criteria Method (QUALIFLEX) is used for measuring sustainable energy investment alternatives by the several emission levels. Forecasted values of 29 provinces in China are converted into the linguistic and fuzzy numbers based on IT2 FS respectively to measure the priorities of emission reduction for sustainable economies. The novelty of this paper is to propose a hybrid decision-making approach based on quadratic modeling and the QUALIFLEX method and to discuss the overall energy emission trend and policies for sustainable economic growth. The results demonstrate that emission reduction policies are the most important phenomenon and the environmental factors should be widely considered to construct sustainable energy investments and production.

2019 ◽  
Vol 11 (13) ◽  
pp. 3514 ◽  
Author(s):  
Tang ◽  
Dinçer

: The purpose of the study is to evaluate the sustainable energy investments based on house of quality. For that, a hybrid decision-making approach to interval type 2 (IT2) fuzzy sets under the hesitancy is proposed. The novelties of the study are to construct an integrated IT2-based modelling and a set of dimensions and criteria for the sustainable energy investments for the emerging countries. The DEMATEL method is used for weighting the customer expectations of sustainable energy investments. The TOPSIS method is applied for ranking the house-of-quality-based investment policies with the technical requirements for the emerging economies. The results show that the capacity issue of energy industry is the most prominent issue for the technical requirements of energy investments. However, it is concluded that increasing communication with the capacity facilities is the most valuable strategy based on the house of quality evaluation. The results are also discussed for further studies and sustainable policies.


2017 ◽  
Vol 6 (3) ◽  
pp. 124-137 ◽  
Author(s):  
Lazim Abdullah ◽  
Liana Najib

Selecting sustainable energy sources is one of the efforts to ensuring optimum energy consumption. However, the selection process is not straight forward as it requires multi-criteria that inherited uncertainty and qualitative evaluation. Multi-criteria evaluation that based on fuzzy set theory is one of the well-known methods to handle uncertainty in decision making and vagueness of information. This paper develops a preference for sustainable energy using the linguistic evaluation of interval type-2 fuzzy analytic hierarchy process (IT2 FAHP). Seven alternatives of sustainable energy sources that closely related to nine criteria were identified as the hierarchical structure of the decision making problem. Two academicians and an engineer attached to government agencies were invited to provide linguistic evaluation. The linguistic evaluations were analyzed using the newly developed IT2 FAHP. The seven-step computational method was implemented and the results suggest that solar energy is the best alternative in selecting the viable sustainable energy.


2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.


2021 ◽  
pp. 1-28
Author(s):  
Ashraf Norouzi ◽  
Hossein Razavi hajiagha

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.


2014 ◽  
Vol 13 (05) ◽  
pp. 979-1012 ◽  
Author(s):  
Ting-Yu Chen

Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with uncertain linguistic variables and their transformation to interval type-2 trapezoidal fuzzy numbers. Concerning the relative importance of multiple decision-makers and group consensus of fuzzy opinions, a procedure using hybrid averages is then employed to construct a collective decision matrix. By an appropriate extension of the classical SAW approach, this paper utilizes the concept of signed distances and establishes an integrated programming model to manage multi-criteria group decisions under the incomplete and inconsistent preference structure. Further, an interactive procedure is established for group decision making. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a collaborative decision-making problem of patient-centered care (PCC).


2017 ◽  
Vol 23 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ting-Yu CHEN

The theory of interval type-2 fuzzy sets provides an intuitive and computationally feasible method of addressing uncertain and ambiguous information in decision-making fields. This paper aims to develop a prioritised interval type-2 fuzzy aggregation operator and apply it to multiple criteria decision analysis with prioritised criteria. This paper considers situations in which a relationship between the criteria exists such that a lack of satisfaction by the higher priority criteria cannot be readily compensated by the satisfaction of lower priority criteria. This paper introduces the developed prioritised interval type-2 fuzzy aggregation operator to address the problem of criteria aggregation in this environment. To demonstrate the feasibility of the proposed operator, this paper provides a multiple criteria decision-making method that uses the prioritised interval type-2 fuzzy aggregation operator, and the method is illustrated with a practical application to landfill site selection.


2019 ◽  
Vol 23 (6) ◽  
pp. 390-404 ◽  
Author(s):  
Vahid Mohagheghi ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė ◽  
Yahya Dorfeshan

Project management is a process that is involved with making important decisions under uncertainty. In project management often the existing data is limited and vague. Sustainable project selection has a multi-criteria evaluation nature which calls for attending to various often conflicting factors under vagueness. To deal with sustainable project selection several important factors should be properly considered. In this paper, in order to provide a new multi-criteria project selection method, a novel last aggregation method is presented. This method has several main novelties. First, to address uncertainty interval type 2 fuzzy sets (IT2FSs) are used. Second, the importance of criteria is investigated by using IT2F entropy. Third, a novel index for decision making is presented that has the merits of ratio system in MOORA and COPRAS, named MORAS. Fourth, the weights of decision makers are computed according to the obtained judgments and the weights are employed to aggregate the results. Fifth, the defuzzification is carried out in the last step of the process by means of a new IT2F ranking method. To present the applicability of the method, it is used in an existing case study in the literature and the outcomes are presented.


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