A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information

Mousavi, M.; Gitinavard, Hossein; Mousavi, Seyed Meysam

doi:10.1016/j.rser.2016.09.125

Cited by 92 publications

(46 citation statements)

References 74 publications

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“…(3) Last, this period has been the most remarkable wherein 6 papers are identified [81,109,170,181,203,214]. Firstly, Maté et al [181] explored the opportunities to adopt more intelligent ways of managing existing RES.…”

Section: Results and In-depth Analysismentioning

confidence: 99%

“…The authors [214] stated that this paradigm will certainly help key stakeholders (e.g., utilities, vendors, laboratories, and universities) to improve their innovation performance. Uniquely, Mousavi et al [81] proposed the only approach computing the relative importance of each energy decision maker or expert during their participation in a GDM renewable energy policy selection problem throughout a hesitant fuzzy modified preferences selection index method. Finally, Mosannenzadeh et al [170] developed an innovative learning methodology to predict barriers to implementation of smart and sustainable urban energy projects.…”

Section: Results and In-depth Analysismentioning

confidence: 99%

“…Energy planning regional [18,22,24,26,61,62], local [19,30,[63][64][65][66][67], urban [68][69][70], rural [71][72][73][74][75][76][77] C1.2. Energy policy planning [37,78,79], evaluation [43,52,80,81], frameworks [82,83] C1.3. Environmental impact analysis environmental and ecological decision-making [84][85][86], life-cycle assessment [2, 87] C1.4.…”

Section: An Overview Of Reviews On Epdmmentioning

confidence: 99%

See 2 more Smart Citations

Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support

Sellak¹,

Ouhbi²,

Frikh

et al. 2017

Renewable and Sustainable Energy Reviews

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Achieving sustainable energy planning and development involves complex decision-making processes. The energy planning decision-making (EPDM) field relies on a plethora of decision analysis methods that offered many solutions to process a variety of energy management and strategic decision-making problems. However, current EPDM solutions are unable to overcome the increasing complexity of strategic energy planning situations involving a large number of stakeholders in uncertain, dynamic, and distributed environments. This raises significant new challenges for researchers in both decision sciences and renewable and sustainable energy planning. On the basis of a representative assortment of peer-reviewed related literature selected by querying multiple electronic databases and indexed in Scopus and Web of Science databases domain journals over the last 12 years, this paper exhaustively highlights and discusses limitations of existing strategic EPDM solutions. The analysis is based on a classification specially developed by holistically harmonizing important domain concepts to categorize the considered representative sample of the field of interest. Additionally, this paper integrates results and conclusions from some recent and most cited literature reviews to (i) formulate essential evidence as well as practical and conclusive literature's supportalongside with the formulated representative sample -to this paper's subsequent insights and statements, and (ii) guarantee that no relevant articles have been excluded. A total of 78 related works is gathered and analyzed to provide a general view and discussion on major complexities found in classical/traditional strategic EPDM solutions and challenges for next-generation EPDM solutions. Moreover, a comparative analysis of the two solutions and a set of "quality indexes" of a next-generation EPDM solution were identified and some proposals were made to improve future applicative research. As an original result coming from the "quality indexes" identified through the review process, an intelligent expert-based framework for next-generation EPDM solutions is developed for enhanced renewable and sustainable energy planning.

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Section: Results and In-depth Analysismentioning

confidence: 99%

Section: Results and In-depth Analysismentioning

confidence: 99%

Section: An Overview Of Reviews On Epdmmentioning

confidence: 99%

See 1 more Smart Citation

Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support

Sellak¹,

Ouhbi²,

Frikh

et al. 2017

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

show abstract

“…Many scholars have used fuzzy sets theory to address uncertainty in project evaluation and selection problems [20][21][22][23][24] . Over the years, a large number of fuzzy multi-criteria decision making (FMCDM) techniques have been developed that differ in areas such as the type of questions asked, theoretical background, and sort of obtained results [25][26][27][28][29][30] . They are all mainly concerned with making the process better informed and structured.…”

Section: Environmental Impact Assessment (Eia)mentioning

confidence: 99%

A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study

Mohagheghi¹,

Mousavi²,

Aghamohagheghi³

et al. 2017

IJCIS

Self Cite

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Selecting transport project to invest is an important task. This paper offers a new sustainable transport investment selection approach that applies interval-valued fuzzy sets (IVFSs) to address uncertainty. Relative preference relation is employed to address importance of criteria. Judgments of experts are given a weight based on all the gathered judgments and the expertise of experts. Furthermore, the concept of Prospect theory is used to rank the alternatives. The approach is applied to a case study and the results are discussed.

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“…To start with outranking method, ELECTRE (ELimination and Choice Expressing the Reality) was created by Roy [14]. Some outranking approaches, based on ELECTRE as well-known model, were reported in recent years i.e., [15,16]. Hashemi et al [17] utilized the interval-valued intuitionistic fuzzy (IVF)-ELECTRE III as a suitable choice, keeping in mind the end goal to illuminate an investment project selection problem.…”

Section: Introductionmentioning

confidence: 99%

A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem

et al. 2018

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This study introduces a new decision model with multi-criteria analysis by a group of decision makers (DMs) with intuitionistic fuzzy sets (IFSs). The presented model depends on a new integration of IFSs theory, ELECTRE and VIKOR along with grey relational analysis (GRA). To portray uncertain real-life situations and take account of complex decision problem, multi-criteria group decision-making (MCGDM) model by totally unknown importance are introduced with IF-setting. Hence, a weighting method depended on Entropy and IFSs, is developed to present the weights of DMs and evaluation factors. A new ranking approach is provided for prioritizing the alternatives. To indicate the applicability of the presented new decision model, an industrial application for assessing contractors in the construction industry is given and discussed from the recent literature.

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A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information

Cited by 92 publications

References 74 publications

Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support

Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support

A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study

A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem

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