Outranking Methods: Promethee I and Promethee II

Goswami, Shankha Shubhra

doi:10.2478/fman-2020-0008

Cited by 37 publications

(17 citation statements)

References 60 publications

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“…The preference ranking organization method for enrichment evaluations (PROMETHEE) is an MCDM tool that enables users to examine and rank alternatives according to their criteria. The PROMETHEE method was developed by Brans and Vince in 1985 [ 49 ] to compare available alternatives based on the selected criteria [ 50 ]. It is favored over other MCDM techniques, such as the analytic hierarchy process and the methodology for ordering performance according to resemblance to the ideal solution [ 51 ].…”

Section: Methodsmentioning

confidence: 99%

Breast Cancer Screening Based on Supervised Learning and Multi-Criteria Decision-Making

Mustapha

Ozsahin

et al. 2022

Diagnostics

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On average, breast cancer kills one woman per minute. However, there are more reasons for optimism than ever before. When diagnosed early, patients with breast cancer have a better chance of survival. This study aims to employ a novel approach that combines artificial intelligence and a multi-criteria decision-making method for a more robust evaluation of machine learning models. The proposed machine learning techniques comprise various supervised learning algorithms, while the multi-criteria decision-making technique implemented includes the Preference Ranking Organization Method for Enrichment Evaluations. The Support Vector Machine, having achieved a net outranking flow of 0.1022, is ranked as the most favorable model for the early detection of breast cancer. The net outranking flow is the balance between the positive and negative outranking flows. This indicates that the higher the net flow, the better the alternative. K-nearest neighbor, logistic regression, and random forest classifier ranked second, third, and fourth, with net flows of 0.0316, −0.0032, and −0.0541, respectively. The least preferred alternative is the naive Bayes classifier with a net flow of −0.0766. The results obtained in this study indicate the use of the proposed method in making a desirable decision when selecting the most appropriate machine learning model. This gives the decision-maker the option of introducing new criteria into the decision-making process.

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Section: Methodsmentioning

confidence: 99%

Breast Cancer Screening Based on Supervised Learning and Multi-Criteria Decision-Making

Mustapha

Ozsahin

et al. 2022

Diagnostics

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“…Walaupun mampu digunakan dalam menganalisa masalah yang kompleks, namun proses dalam metode AHP ini cukup sederhana. Penerapan AHP umumnya melalui empat langkah [11], [12] b. Tetapkan prioritas pada elemen-elemen pada hirarki. Langkah ini memanfaatkan pendapat para ahli serta dapat menampung pula pendapat yang bersifat kualitatif.…”

Section: Metode Analytical Hierarchy Process (Ahp)unclassified

Masalah Tata Letak Fasilitas Logistik Dengan Menggunakan Fuzzy Dynamic Analitycal Hierarchy Process (Fdahp)

Arifin¹,

Martianingsih²

2022

JUISIK

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Pada penentuan aliran barang dengan metode Activity Relationship Chart (ARC) adalah ditentukannya nilai rating untuk menempatkan suatu unit dengan unit lain. Biasanya nilai rating itu bersifat mutlak, sangat penting, penting, cukup, tidak penting dan tidak dikehendaki. Permasalahannya adalah dalam menentukan nilai sangat penting , penting , cukup dan tidak penting ketika masalah tata letak fasilitas logistik akan di implementasikan. Dalam penelitian ini, ingin dikembangkan suatu metode dalam menentukan nilai riil dari ARC dengan menggunakan pendekatan teori fuzzy dan perbandingan berpasangan dari AHP dengan model penilaian dinamis untuk menilai tingkat konsistensi dari perencana. Hasil Akhir penelitian ini diharapkan diperolehnya suatu model yang mampu memberikan nilai yang lebih tepat dari permasalahan penempatan fasilitas atau departemen pada suatu perusahaan. Untuk menguji keakurasian model maka dilakukan dengan menggunakan simulasi komputer.

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“…Over the last few decades, MCDM has become an important decision-making tool in number of diverse areas including manufacturing, 1 trade, economic, 2 health and education, 3,4 domestic 5,6 etc. Several researchers are actively focusing on this field to update different MCDM strategies and to fill up the gaps that occur in previous approaches.…”

Section: Introductionmentioning

confidence: 99%

Development of entropy embedded COPRAS-ARAS hybrid MCDM model for optimizing EDM parameters while machining high carbon chromium steel plate

Goswami

Behera

Mitra

et al. 2022

Advances in Mechanical Engineering

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The purpose of this paper is to discuss the optimization of electrical discharge machining (EDM) parameters in a green production environment. The primary goal of this work is to create a novel hybrid multi-criteria decision making (MCDM) model that combines COPRAS and ARAS to determine the best input EDM parameters for machining high carbon chromium tool steel plate. To carry out the selection process, a total of nine tests were carried out using four input parameters, including dielectric level, peak current, flushing pressure, and pulse duration at three different levels of magnitude, and the readings of the respective five output parameters were measured. The weights of these five criterions are evaluated using entropy, while COPRAS-ARAS hybrid model is implemented to choose the best alternative experiment among these nine availabilities. Experiment 5 is found to be the best choice, with the machining parameters 261 µs pulse length, 0.3 kg/cm2 flushing pressure, 4.5 Å current, and 80 mm dielectric level being the optimal input values. The primary result demonstrates that the developed hybrid model is sufficiently accurate and provides the best choice when compared to six existing MCDM tools. Finally, sensitivity analysis is used to justify the hybrid model’s stability and consistency.

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Outranking Methods: Promethee I and Promethee II

Cited by 37 publications

References 60 publications

Breast Cancer Screening Based on Supervised Learning and Multi-Criteria Decision-Making

Breast Cancer Screening Based on Supervised Learning and Multi-Criteria Decision-Making

Masalah Tata Letak Fasilitas Logistik Dengan Menggunakan Fuzzy Dynamic Analitycal Hierarchy Process (Fdahp)

Development of entropy embedded COPRAS-ARAS hybrid MCDM model for optimizing EDM parameters while machining high carbon chromium steel plate

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