Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study

Gitinavard, Hossein; Mousavi, Seyed Meysam; Vahdani, Behnam

doi:10.1016/j.energy.2016.10.070

Cited by 41 publications

(15 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering all the above "quality indexes" and examining the results of the review, only nine papers [49,109,167,170,181,192,203,206,215] were deemed appropriate (where the authors differently addressed some EPDM problems that have been classically or not solved at all by the community), despite one of them are more energy management oriented solution [181] and none of them exactly satisfies all (or at least 50%) the above requirements.…”

Section: Results and In-depth Analysismentioning

confidence: 99%

“…Firstly, in only two of these articles the authors proposed a DSS [49,170], one is a computerized tool [192], instead the rest is standalone decision-making approaches or theoretical decision-making frameworks [109,167,181,203,206,215]. Besides, in Simão et al [49] even if a hybrid Web-based multiple criteria DSS (interactive, data, model, communications, and knowledge-driven) is proposed-to support public participation in distributed collaborative planning using a learning environment -the authors covered only two strategic EPDM categories (at best C1.4 and C1.5) and two stages (at best S1 and S3), nor considered components to deal with encountered uncertainty situations in such complex participatory decision-making problems.…”

Section: Results and In-depth Analysismentioning

confidence: 99%

“…The remaining two types of uncertainty, UT1-Random uncertainty (e.g., [183,214]) and UT3-Grey uncertainty (e.g., [19,88]) are less treated by researchers in strategic EPDM (11% and 16%, respectively). Therefore, in most case studies, the uncertainties have been handled throughout (1) fuzzy linguistic (38%) or (2) fuzzy (23%) decision-making environments while considering other types of preferences' representation (e.g., intervals [199,215], intuitionistic [111,197], or trapezoidal fuzzy numbers [41]). The remaining articles address uncertainty (mostly in an MCDM context) by carrying out sensitivity analysis (26%), monte carlo simulation (5%), or scenario analysis (3%) of the criteria weighting as a way to check the robustness of the results.…”

Section: Results and In-depth Analysismentioning

confidence: 99%

“…Hence, the most innovative standalone decision-making approaches can be ascribed to the following papers [109,167,181,203,206,215]: Öztayşi and Kahraman [167] proposed one of the first attempt that investigated the use of different and recent fuzzy sets (interval type-2 and hesitant fuzzy sets) in a strategic EPDM problem (C1.4); Abaei et al [109] and Ghosh et al [203] proposed one of the most innovative decision-making approaches to solve site selection problems (C1.5), using BN and influence diagram, and ANNs, respectively; Maté et al [181] proposed advanced data analytics tools (energy consumption behaviors using data mining and big data), predictive AI models (ANNs), and an innovative knowledge management using an information extraction system (even if it is not 100% strategic EPDM oriented study); whereas, Gitinavard et al [215] is the only attempt to handle partially and completely unknown criteria weights information while combining multiple classical uncertainty solutions (fuzzy environment and sensitivity analysis). However, each of them presents some limitations: while the first four [109,167,181,203] present apparently single decision maker models with limited capabilities to handle all types of uncertainty, the remaining paper [215] presents a classical GDM model where an aggregation approach is applied to combine the preferences of different decision makers resulting information loss and distortion (caused by unifying heterogeneous information) [227].…”

Section: Results and In-depth Analysismentioning

confidence: 99%

See 3 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

View full text Add to dashboard Cite

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.

show abstract

Section: Results and In-depth Analysismentioning

confidence: 99%

Section: Results and In-depth Analysismentioning

confidence: 99%

Section: Results and In-depth Analysismentioning

confidence: 99%

Section: Results and In-depth Analysismentioning

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

View full text Add to dashboard Cite

show abstract

“…, 5). 530 Then, by (25), the uncertain linguistic collective decision 531 matrixX = x i j 4×9 is yielded and presented in Table VII. 532 TABLE IV LINGUISTIC RATINGS OF ALTERNATIVES PROVIDED BY EXPERT GROUPS TABLE V THE TOTAL-RELATION MATRIX T TABLE VI INFLUENCES of unfair assessments on the optimal EVCS site results can 566 be evidently seen in the rank orderings derived in the cases of 567 "minimum" and "maximum".…”

mentioning

confidence: 99%