Sensitivity analysis for multi‐attribute system selection problems in onshore Environmentally Friendly Drilling (EFD)

Yu, Ok-Youn; Guikema, Seth D.; Briaud, J-L; Burnett, David

doi:10.1002/sys.20200

Cited by 14 publications

(4 citation statements)

References 8 publications

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“…Verification of consistency has also been considered by most of the researchers (Triantaphyllou and Mann, 1989;Pamučar et al, 2017). Yu et al (2012) performed sensitivity analysis for the weightages of the attributes and for the uncertainty for the attributes. The application area for the sensitivity analysis is the selection of onshore environmentally friendly drilling systems.…”

Section: Application Of Proposed Mcda Technique On the Case Studymentioning

confidence: 99%

A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

Bandyopadhyay

2023

Prog Artif Intell

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This paper has proposed a novel Multi-Criteria Decision Analysis (MCDA) technique that considers relationships among the criteria, relationships among the alternatives, relationships among the criteria and the alternatives, the uncertainty or dilemma that the decision makers face in their decision-making, the entropy among the criteria. These characteristics seem to be the essential characteristics of various MCDA techniques as evident from the existing literature. The dilemma of the decision makers have been captured by the use of Hesitant Fuzzy Elements; the information content among the criteria have been captured by applying the concept of entropy through the application of a technique called IDOCRIW. Relationships have been determined by calculating the covariances among the criteria and among the alternatives. A kind of sensitivity analysis, rank reversal method has been performed to verify the effectiveness of the proposed technique. The proposed method has also been compared with four different types of already existing MCDA techniques, AHP, MAUT, MACBETH and MOORA. Both the sensitivity analysis and the comparison with other methods establish the effectiveness of the proposed technique.

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Section: Application Of Proposed Mcda Technique On the Case Studymentioning

confidence: 99%

A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

Bandyopadhyay

2023

Prog Artif Intell

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“…However, each performance value could be affected by uncertain factors. Several approaches have been presented for analyzing how the uncertainty in the performance values (the input) affects the ranking of the objects (the output; Corrente, Figueira, & Greco, 2014;Hyde & Maier, 2006;Hyde, Maier, & Colby, 2004;Rocco & Tarantola, 2014;Yu, Guikema, Briaud, & Burnett, 2012). The approaches, based on Monte Carlo simulation, consider each uncertain factor as a random variable with known probability density functions.…”

Section: Lexicographic Average Rank For Evaluating Uncertain Multi-inmentioning

confidence: 99%

Risk-based ROI, capital budgeting, and portfolio optimization in the Department of Defense

Mun

2020

Defense ARJ

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This article shows a reusable, extensible, adaptable, and comprehensive advanced analytical modeling process to help the U.S. Department of Defense (DoD) with risk-based capital budgeting and optimizing of acquisition and program portfolios with multiple stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The article covers traditional capital budgeting methodologies in industry and explains how these methods can be applied in the DoD by using DoD-centric, noneconomic, logistic, readiness, capabilities, and requirements variables. Portfolio optimization for the purposes of selecting the best combination of programs and capabilities is also addressed, as are alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. Finally, an illustration from the Program Executive Office Integrated Warfare Systems (PEO-IWS) and Naval Sea Systems Command (NAVSEA) showcases the methodology’s application in developing a comprehensive and analytically robust case study that senior leadership at the DoD may utilize to make optimal decisions.

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“…In theory, some MADM methods based on statistics and probability can be regarded as probabilistic linkage to different databases (Comber & Arribas‐Bel, 2019), and their performance depends greatly on the completeness and accuracy of data (Zhu et al, 2016). In addition, faced with many decision variables, some MADM methods encounter difficulty in the selection and calculation of attributes (Yu, Guikema, Briaud, & Burnett, 2012). Therefore, due to the lack of uniform and strict standards for POIs and the inaccurate description of some text attributes, MADM methods have difficulty ensuring stable and ideal accuracy.…”

Section: Introductionmentioning

confidence: 99%

A points of interest matching method using a multivariate weighting function with gradient descent optimization

Yang

Wang

Zhang

et al. 2020

Transactions in GIS

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Volunteered geographic information contains abundant valuable data, which can be applied to various spatiotemporal geographical analyses. While the useful information may be distributed in different, low‐quality data sources, this issue can be solved by data integration. Generally, the primary task of integration is data matching. Unfortunately, due to the complexity and irregularities of multi‐source data, existing studies have found it difficult to efficiently establish the correspondence between different sources. Therefore, we present a multi‐stage method to match multi‐source data using points of interest. A spatial filter is constructed to obtain candidate sets for geographical entities. The weights of non‐spatial characteristics are examined by a machine learning‐related algorithm with artificially labeled random samples. A case study on Fuzhou reveals that an average of 95% of instances are accurately matched. Thus, our study provides a novel solution for researchers who are engaged in data mining and related work to accurately match multi‐source data via knowledge obtained by the idea and methods of machine learning.

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Sensitivity analysis for multi‐attribute system selection problems in onshore Environmentally Friendly Drilling (EFD)

Cited by 14 publications

References 8 publications

A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

Risk-based ROI, capital budgeting, and portfolio optimization in the Department of Defense

A points of interest matching method using a multivariate weighting function with gradient descent optimization

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