Multicriteria Decision Analysis: Overview and Implications for Environmental Decision Making

Hermans, Caroline; Erickson, Jon D.

doi:10.1016/s1569-3740(07)07010-1

Cited by 17 publications

(8 citation statements)

References 34 publications

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“…For example, methods from multi-attribute utility theory such as the analytical hierarchy process or simple additive weighting require a global preference to be established for the entire group (Hermans and Erickson, 2007). The method is also easy to understand with a high degree of transparency.…”

Section: Resultsmentioning

confidence: 99%

Collaborative environmental planning in river management: An application of multicriteria decision analysis in the White River Watershed in Vermont

Hermans

Erickson

Noordewier

et al. 2007

Journal of Environmental Management

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Section: Resultsmentioning

confidence: 99%

Collaborative environmental planning in river management: An application of multicriteria decision analysis in the White River Watershed in Vermont

Hermans

Erickson

Noordewier

et al. 2007

Journal of Environmental Management

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“…In addition, it was found that PROMETHEE rankings to be more stable than ELECTRE rankings. (Brans, Vincke, & Mareschal, 1986) (Hermans & Erickson, 2007)…”

Section: Selection Of the Promethee Methodsmentioning

confidence: 99%

A multi-criteria decision making approach to the new product development process in industry

Youssef¹,

Webster

2022

Rep. Mech. Eng.

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New product development is the process of taking a new idea and turning that idea into an actual product, available on the market. This process includes a number of stages, starting with the product concept and increasingly refining that concept until it becomes the final product and is ready for marketing. The primary function of a Multi-Criteria Decision Making approach is to take the values of a set of criteria and determine an optimal course of action. This research aims to evaluate the significance of using such the PROMETHEE approach to formulate the new product development process within an organization. In order to use that approach to assess the level of improvement that the organization has seen in its performance in new product development, and to estimate the possible level of improvement that might take place if the organization implements suggested recommendations. A research case is studied in order to make this assessment. Results of the case study are presented to demonstrate the feasibility of using a Multi-Criteria Decision Making approach for improving the new product development process within a real-world industrial setting.

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“…Brans in 1982, uses pairwise comparisons and "values outranking relations" to select the best alternative [94]. PROMETHEE II can support DMs to reach an agreement on feasible alternatives over multiple criteria from different perspectives [95,96]. In the PROMETHEE II method, a Complexity positive outranking flow reveals that the chosen alternative outranks all alternatives, whereas a negative outranking flow reveals that the chosen alternative is outranked by all alternatives [51,97].…”

Section: Promethee II Promethee Ii Proposed Bymentioning

confidence: 99%

Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM

Zhang

Kou

et al. 2020

Complexity

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In many disciplines, the evaluation of algorithms for processing massive data is a challenging research issue. However, different algorithms can produce different or even conflicting evaluation performance, and this phenomenon has not been fully investigated. The motivation of this paper aims to propose a solution scheme for the evaluation of clustering algorithms to reconcile different or even conflicting evaluation performance. The goal of this research is to propose and develop a model, called decision-making support for evaluation of clustering algorithms (DMSECA), to evaluate clustering algorithms by merging expert wisdom in order to reconcile differences in their evaluation performance for information fusion during a complex decision-making process. The proposed model is tested and verified by an experimental study using six clustering algorithms, nine external measures, and four MCDM methods on 20 UCI data sets, including a total of 18,310 instances and 313 attributes. The proposed model can generate a list of algorithm priorities to produce an optimal ranking scheme, which can satisfy the decision preferences of all the participants. The results indicate our developed model is an effective tool for selecting the most appropriate clustering algorithms for given data sets. Furthermore, our proposed model can reconcile different or even conflicting evaluation performance to reach a group agreement in a complex decision-making environment.

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Multicriteria Decision Analysis: Overview and Implications for Environmental Decision Making

Cited by 17 publications

References 34 publications

Collaborative environmental planning in river management: An application of multicriteria decision analysis in the White River Watershed in Vermont

Collaborative environmental planning in river management: An application of multicriteria decision analysis in the White River Watershed in Vermont

A multi-criteria decision making approach to the new product development process in industry

Decision-Making Support for the Evaluation of Clustering Algorithms Based on MCDM

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