SMART Method

Alinezhad, Alireza; Khalili, Javad

doi:10.1007/978-3-030-15009-9_1

Cited by 11 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The value of the preference function is calculated according to the function type specified by the decision-maker. Six types of preference functions exist (Alinezhad and Khalili 2019 ; Ishizaka and Nemery 2013 ). : Usual criterion: if the difference , alternative is preferred over with preference , otherwise 0.…”

Section: Methodology and Datamentioning

confidence: 99%

“…If the difference and , alternative is preferred over with preference , otherwise . Gaussian criterion: the preference is calculated via Gaussian curve (more details about this type of criterion and PROMETHEE methods are in (Alinezhad and Khalili 2019 ) or in (Ishizaka and Nemery 2013 ). …”

Section: Methodology and Datamentioning

confidence: 99%

“…PROMETHEE I compares the positive and negative flows for each pair of alternatives—if the positive flow of alternative is higher or equal than the positive flow of alternative and if the negative flow of alternative is lower or equal than the negative flow of alternative , then is preferred over ; when both flows for both alternatives are equal, then the alternatives are indifferent. Otherwise, the alternatives are incomparable (Alinezhad and Khalili 2019 ; Ishizaka and Nemery 2013 ; Brans and Mareschal 2005 ).…”

Section: Methodology and Datamentioning

confidence: 99%

See 2 more Smart Citations

Two-stage weighted PROMETHEE II with results’ visualization

Kuncová

Seknickova

2021

Cent Eur J Oper Res

View full text Add to dashboard Cite

Multicriteria decision-making methods are widely spread and used to assist the decision-makers to resolve problems. Many of the methods are simple to deploy (WSA, TOPSIS), which is an advantage and because of the computer boom, there is no problem with calculations. However, more sophisticated methods are evolving. The modelling of preferences is improved (from linear in WSA to Gaussian in PROMETHEE), multilevel decision-making (such as AHP) is extended to modelling of dependencies between individual criteria (ANP). The presented method, two-stage weighted PROMETHEE, combines the advantages of generalized preferential functions in PROMETHEE methods, unambiguous arrangement (PROMETHEE II) and hierarchical approach (AHP). In addition, this paper demonstrates the application of the method to evaluate the order of 14 regions of the Czech Republic in regard to economic indices such as the unemployment rate, economic activity, average age, wages, free working places, income, consumption and investments. Data are taken from the Czech Statistical Office web and include the years 2012–2019. In the first stage, the position of each region is calculated; in the second stage, all years mentioned are considered, including the aspect of the weighted time series. Result visualization is made possible using the Visual PROMETHEE software.

show abstract

Section: Methodology and Datamentioning

confidence: 99%

Section: Methodology and Datamentioning

confidence: 99%

Section: Methodology and Datamentioning

confidence: 99%

See 1 more Smart Citation

Two-stage weighted PROMETHEE II with results’ visualization

Kuncová

Seknickova

2021

Cent Eur J Oper Res

View full text Add to dashboard Cite

show abstract

“…For each criterion f j symbol

denotes the highest value of this criterion,

, and

denotes the lowest value of this criterion,

. According to the data

for each alternative (here districts) a i and each criterion f j the normalized values

are calculated [ 82 ]:

The final ranking is based on the utility—the higher is the better:

The steps are described below on example of the 3rd area (Demographical changes) with 3 criteria: 3_a: Share of foreigners by country of origin (%); 3_b: Age index (%); 3_c: Urbanization rate (%), Evaluation using WSA starts with data matrix Y (short version is in Table A2 ) where the lowest (minimum) and highest (maximum) values are found. Then the matrix is normalized ( Table A3 ) using Formulas (A2) for the first two criteria (which should be minimized) and Formula (A1) for the third criterion (which is of the maximization type).…”

Section: Table A1mentioning

confidence: 99%

Inequalities in Health: Methodological Approaches to Spatial Differentiation

Hübelová

Kuncová

Vojáčková

et al. 2021

IJERPH

View full text Add to dashboard Cite

The prevalence of inequalities in the general health position of communities can be assessed by using selected determinants. The aims of this article are three-fold: (1) to apply a comprehensive approach to the assessment of inequalities in the general health position of communities, (2) to determine the spatial differentiation of determinants, and (3) to present selected assessment methods and their impact on the results. To present a quantitative assessment of these inequalities in health status in communities, a composite indicator (Health Index) was developed. This Health Index is composed of 8 areas of evaluation and 60 indicators which include, amongst others, determinants of health status and healthcare at district level (LAU 1) in the Czech Republic. The data are evaluated using multicriteria decision-making methods (the WSA and TOPSIS methods). Findings suggest that, when all eight domains are assigned the same weight of one, the spatial differentiation among the districts is similar when using both methods. If different weightings are assigned to the districts, changes occur in both the index values and the rankings of the analyzed districts. For example, the allocation of weightings in both methods results in a rearrangement of the ranking of districts for which the Health Index is around the average.

show abstract

“…The main focus has been on the presentation of the methods and respective software themselves (see e.g. Weistroffer and Li ( 2016 ), Alinezhad and Khalili ( 2019 ) and Ishizaka and Nemery ( 2013 )). A recent article by Mustajoki and Marttunen ( 2017 ) compared 23 software for supporting environmental planning processes, and focused on their capability to support the different MCDA stages.…”

Section: Revisiting Uncertainty and Sensitivity Analysis In Cismentioning

confidence: 99%

MCDA Index Tool: an interactive software to develop indices and rankings

Cinelli

Spada

Kim³

et al. 2020

Environ Syst Decis

View full text Add to dashboard Cite

A web-based software, called MCDA Index Tool (https ://www.mcdai ndex.net/), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices' scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers' and stakeholders' preferences.

show abstract

SMART Method

Cited by 11 publications

References 0 publications

Two-stage weighted PROMETHEE II with results’ visualization

Two-stage weighted PROMETHEE II with results’ visualization

Inequalities in Health: Methodological Approaches to Spatial Differentiation

MCDA Index Tool: an interactive software to develop indices and rankings

Contact Info

Product

Resources

About