Project rankings for participatory budget based on the fuzzy TOPSIS method

Walczak, Dariusz; Rutkowska, Aleksandra

doi:10.1016/j.ejor.2016.12.044

Cited by 95 publications

(39 citation statements)

References 33 publications

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“…The fuzzy pay-off method was used by Sarkar and Mahapatra [8] to form a fuzzy pay-off distribution for an investment that is compatible with the requirements set by the circumstances surrounding giga-investments. The "Technique for Order Preference by Similarity to Ideal Solution" was used for city investment project rankings by Collan et al [9]. In their paper, a fuzzy technique is proposed for order preferences, based on the similarity to an ideal solution.…”

Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

2019

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As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance.

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Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

2019

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“…The greater this ratio is, the closer the alternative is to the ideal solution and the farther it is from the anti-ideal solution. Even after 2010, studies using the non-hybrid versions of TOPSIS have been undertaken [24][25][26][27][28][29][30][31][32][33][34][35]. Similar to AHP, these TOPSIS studies can be roughly categorized as methodological improvement studies and model application studies.…”

Section: Literature Reviewmentioning

confidence: 99%

Rank-Based Comparative Research Flow Benchmarking the Effectiveness of AHP–GTMA on Aiding Decisions of Shredder Selection by Reference to AHP–TOPSIS

et al. 2018

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The AHP–GTMA (analytic hierarchy process and graph theory and matrix approach) has been applied to select the best paper shredder before a company was making a bulk purchase order. However, there is a question as to whether one such relatively recent approach is effective to aid the selection decision problems in industrial/commercial practice. In this paper, a novel multi-measure, rank-based comparative research flow is proposed. The real decision problem case mentioned above is solved using the AHP–GTMA and the AHP–TOPSIS methods, respectively, with relevant datasets sourced. Several measures in the proposed flow, i.e., the arithmetical, geometrical, or even statistical ones, are multiplexed and used to validate the similarity between the rank order vectors (ROVs) (and thus between the final preferential orders determined over the alternatives) that are obtained using these two different methods. While AHP–TOPSIS is a confident multi-attribute decision-making (MADM) approach which has been successfully applied to many other fields, the similarity validated between these individual results using the proposed method is used to confirm the efficacy of the AHP–GTMA approach and to determine its applicability in practice. In addition, along with this study, some contributable points are also rendered for implementing the decision models, e.g., the optimized recursive implementation in R to compute the permanent value of a square ASAM (alternative selection attribute matrix, which is the computational basis required by AHP–GTMA) of any dimension. The proposed methodological flow to confirm the similarity based on the ordinal rank information is not only convenient in operational practice with ubiquitous tool supports (e.g., the vector-based R statistical platform), but also generalizable (to verify between another pair of results obtained using any other MADM methods). This gives options for future research.

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“…The implementation of such projects entails a risk, as it neglects the outcome of selected CB projects to be completed for the town's sustainable development. Therefore, in order for the CB projects to MCDA methods most frequently used in decisions concerning urban sustainable development are: AHP used in previous studies [11,21,24,25,28,32,35], its fuzzy version (Fuzzy AHP) [9,15,[21][22][23]26,29], and a fuzzy version of the TOPSIS method used in other previous studies [10,11,20,23,26,27,29,31,33,34]. Other examples of the use of decisions made in this manner by means of the ELECTRE method [24], PROMETHEE [28], ANP (Analytic Network Process), Fuzzy DEMATEL (DEcision MAking Trial and Evaluation Laboratory), Fuzzy VIKOR (Vlse Kriterijumska Optimizacija kompromisno Resenje which means multi-criteria optimization and compromise solution, in Serbian) [30], and THOWA (2-Tuple Hybrid Ordered Weighted Averaging) [34].…”

Section: Introductionmentioning

confidence: 99%

“…It is advisable that the emerging decision-making issue be presented to experts who will evaluate the CB projects submitted. To that end, the experts should use available tools, for instance the known methodology MCDA (multi-criteria decision analysis), AHP (Analytic Hierarchy Process) [4,5], PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluation) [6], TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) [7], or their variants operating on fuzzy numbers [8] employed successfully to solve similar decision-making problems [9][10][11]. Such fuzzy approaches to decision making are particularly important in decision-making problems where uncertainty arises [12][13][14].The methodological contribution of this paper is to propose and verify a new MCDA method, called PVM-VSI (Preference Vector Method computed in Vector Space of Increments), based on vector calculations.…”

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confidence: 99%

Use of the PVM Method Computed in Vector Space of Increments in Decision Aiding Related to Urban Development

2019

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The paper presents a possibility to use a new PVM-VSI (Preference Vector Method computed in Vector Space of Increments) method in making decisions that demand that different variants should be considered, while being evaluated with respect to different criteria. Hence, knowledge about them is a must, and that knowledge is not necessarily available quantitatively, whereas the very evaluation should be relatively objective; that is, independent from the decision maker’s preferences or opinions. The paper presents the use of the PVM-VSI method in support decisions related to urban development—to rank projects submitted for implementation within the framework of a citizen budget. The ranking will make it feasible to determine which of the submitted projects will have the dominant influence on the town’s sustainable development, and, subsequently, which ones should be presented to citizens as the better ones out of the projects submitted, and to compare the method mentioned with methods used in similar decision-making problems in the past: Fuzzy AHP (Analytic Hierarchy Process), Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and Fuzzy PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluation).

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Project rankings for participatory budget based on the fuzzy TOPSIS method

Cited by 95 publications

References 33 publications

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

Rank-Based Comparative Research Flow Benchmarking the Effectiveness of AHP–GTMA on Aiding Decisions of Shredder Selection by Reference to AHP–TOPSIS

Use of the PVM Method Computed in Vector Space of Increments in Decision Aiding Related to Urban Development

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