Comparison SAW and MOORA Methods with Attribute Weighting Using Rank Order Centroid in Decision Making

Lubis, Ahmadi Irmansyah; Sihombing, Poltak; Nababan, Erna Budhiarti

doi:10.1109/mecnit48290.2020.9166640

Cited by 28 publications

(19 citation statements)

References 11 publications

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“…Later, in 2005, the preference ranking organization method for evaluation enrichment (PROMETHEE) appeared, which calculates the dominant flows of alternatives [50,51]. Meanwhile, in 2006, the multi-objective optimization method based on ratio analysis (MOORA) appeared, which evaluates the ranking of each alternative based on ratio analysis [52,53]. The most recent of this group are the combinatorial distance-based evaluation (CODAS) models that use the alternative Euclidean distance of the negative ideal and the Taxicab distance [54,55].…”

Section: Multi-criteria Methodsmentioning

confidence: 99%

“…Among the most recent methods of 2017, is the q-rung orthopair (q-ROF) fuzzy set, which is based on IFS and PFN, which presents, in parallel, the degrees of membership, nonmembership, and indeterminacy of decision makers [51,52]. Meanwhile, the T-spherical fuzzy set, from 2019, has the flexibility to unite the sum of the q-th power of membership, abstinence, and non-membership between one and zero [61,62].…”

Section: Multi-criteria Methodsmentioning

confidence: 99%

“…Within the family of metaheuristic algorithms is the mathematical model called particle swarm optimization (PSO) [52]. PSO finds the best spot, based on the group intelligence of flocks of birds and schools of fish, during predation and foraging [15,94].…”

Section: Particle Swarm Algorithm (Pso)mentioning

confidence: 99%

“…The PSO works within a set of solutions (swarm) that contain a working sequence with a series of solutions (particles), where each particle updates its speed, considering past and present locations, to compare them with those of the swarm and thus establish the best global position [52,95].…”

Section: Particle Swarm Algorithm (Pso)mentioning

confidence: 99%

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PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy: A Review

et al. 2022

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Companies are constantly changing in their organization and the way they treat information. In this sense, relevant data analysis processes arise for decision makers. Similarly, to perform decision-making analyses, multi-criteria and metaheuristic methods represent a key tool for such analyses. These analysis methods solve symmetric and asymmetric problems with multiple criteria. In such a way, the symmetry transforms the decision space and reduces the search time. Therefore, the objective of this research is to provide a classification of the applications of multi-criteria and metaheuristic methods. Furthermore, due to the large number of existing methods, the article focuses on the particle swarm algorithm (PSO) and its different extensions. This work is novel since the review of the literature incorporates scientific articles, patents, and copyright registrations with applications of the PSO method. To mention some examples of the most relevant applications of the PSO method; route planning for autonomous vehicles, the optimal application of insulin for a type 1 diabetic patient, robotic harvesting of agricultural products, hybridization with multi-criteria methods, among others. Finally, the contribution of this article is to propose that the PSO method involves the following steps: (a) initialization, (b) update of the local optimal position, and (c) obtaining the best global optimal position. Therefore, this work contributes to researchers not only becoming familiar with the steps, but also being able to implement it quickly. These improvements open new horizons for future lines of research.

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Section: Multi-criteria Methodsmentioning

confidence: 99%

Section: Multi-criteria Methodsmentioning

confidence: 99%

Section: Particle Swarm Algorithm (Pso)mentioning

confidence: 99%

Section: Particle Swarm Algorithm (Pso)mentioning

confidence: 99%

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PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy: A Review

et al. 2022

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“…Metode Rank Order Centroid dan Additive Ratio Assessment, dilakukan pada objek yang berbeda seperti pemilihan Jaksa Terbaik (Ndruru, 2020), Pemilihan Kepala Lingkungan (Handayani, Syahrizal, & Tampubolon, 2019), Penilaian Kinerja Karyawan (Mesran, Afriany, & Sahir, 2019) dan belum ada untuk rekomendasi supplier. Metode ini melakukan perhitungan bobot menggunakan Rank Order Centroid agar pembobotan terhadap kriteria menjadi lebih baik karena ROC merupakan metode sederhana yang dapat menghasilkan nilai bobot terhadap kriteria yang digunakan (Badaruddin, 2019) menghasilkan kinerja tertinggi dalam dalam hal identifikasi alternatif (Ahn, 2011) serta mengatasi proses pembobotan atribut dalam pengambilan keputusan (Lubis, Sihombing, & Nababan, 2020) dan Metode Additive Ratio Assessment yang secara garis besar banyak melakukan perangkingan dengan cara membandingkan dengan alternative lainnya sehingga mendapatkan hasil yang ideal dan terbaik (Zavadskas & Turskis, 2010;Pratiwi et al, 2019;Supriyanto et al, 2019).…”

Section: Pendahuluanunclassified

Penerapan Metode Rank Order Centroid dan Additive Ratio Assessment Pada Aplikasi Rekomendasi Supplier

Addenan

Susanti

2021

Edumatic

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PT.Yanmarindo Perkasa is a company in the sale of diesel engines, generators, tooling tools and engine spare parts. Many suppliers want to distribute their goods through PT.Yanmarindo Perkasa, thus demanding the company to choose the right supplier, in order to ensure the smooth fulfillment of stock items. The process of selecting suppliers is still done manually with criteria limited to quantitative criteria, so that the process takes a long time and the results are not precise. The purpose of this study is to build a decision support system for supplier recommendations quickly and precisely in meeting the company's needs. The supplier selection process uses the Rank-Order Centroid (ROC) method in weighting the criteria and the Additive Ratio Assessment (ARAS) for ranking. ARAS value obtained is the K value that is ranked to get the best supplier by using a computerized decision support system. The application of these two methods can speed up the results of decisions, does not take a long time and the results obtained are also maximum.

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Supplier Selection Process Based on CODAS Method Using q-Rung Orthopair Fuzzy Information

Ramírez-Ochoa

Pérez-Domínguez

Martínez-Gómez

et al. 2022

Q-Rung Orthopair Fuzzy Sets

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Comparison SAW and MOORA Methods with Attribute Weighting Using Rank Order Centroid in Decision Making

Cited by 28 publications

References 11 publications

PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy: A Review

PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy: A Review

Penerapan Metode Rank Order Centroid dan Additive Ratio Assessment Pada Aplikasi Rekomendasi Supplier

Supplier Selection Process Based on CODAS Method Using q-Rung Orthopair Fuzzy Information

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