Review of indicators and multi-criteria decision-making methods for assessing the sustainability of urban mobility

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

Selection of boron based tribological hard coatings using multi-criteria decision making methods

Site Suitability Analysis for Green Hydrogen Production Using Multi-Criteria Decision-Making Methods: A Case Study in The State of Ceará, Brazil

As a significant technology in the automotive manufacturing industry, weight reduction in vehicle design has attracted much attention. Its effect on energy saving and emission reduction is prominent. The application of lightweight material is commonly adopted as a primary way of weight reduction. However, material selection is often subject to multi-perspective performance characteristics, e.g., mechanical and societal properties, and therefore, an effective multi-criteria decision-making (MCDM) method is needed. This paper presents a systematic hierarchical structure of multi-perspective indices for optimal lightweight material selection, including mechanical, durability, societal, and technical properties. A hybrid evaluation approach (G-TOPSIS) integrating grey relation analysis and technique for order performance by similarity to ideal solution (TOPSIS) is applied to evaluate lightweight material alternatives and obtain an optimal one. A case study, i.e., 17 kinds of lightweight materials, is conducted to verify the hierarchical structure and the MCDM method. In addition, a sensitivity analysis is conducted to monitor the robustness of solution ranking to changes. The results show that this method provides an effective decision-making tool for optimal lightweight material selection for automobile applications.

Supplier Selection in Furniture Production Company Using Rough AHP and Rough TOPSIS

Nowadays, firms are trying to execute and use blockchain technology (BT) for rising the products and service goodness in the supply chain (SC). Based on the specific requirements, the BT can be used in several areas. The BT assets various segments of Supply Chain Management (SCM) with consideration of several effective features that are characterized to be multi-criteria decision making (MCDM) issues with environmental restrictions of uncertainty conditions. This research illustrates the suitability of BT in SCM for various segments that are assessed using a neutrosophic model according to single-valued neutrosophic sets (SVNSs). Also, contributes as an evaluation model that combines neutrosophic set, with MCDM methods of Analytic Hierarchy Process (AHP), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). The proposed study uses the AHP method to generate weights of criteria considering the expert's perspectives. Moreover, uses the neutrosophic theory to handle uncertain situations. The alternatives ranked based on outcomes of applying TOPSIS and VIKOR methods. A case study presents a hierarchical MCDM issue of 7 criteria and 20 sub-criteria with alternative segments assessed. As a result, the medicine segment is recommended to be the best alternative according to the proposed methods of AHP, TOPSIS, and VIKOR while the insurance segment is not recommended by AHP and TOPSIS methods and jewelry segments are not recommended in the VIKOR method.

<p><em>The large number of rice varieties raises problems in selecting varieties that have the potential to produce more rice and are resistant to pests and diseases. One way to help the selection of rice varieties is by using a decision support system. This study aims to implement the Analytic Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods in a decision support system to determine which type of rice is superior based on existing alternatives so that it can be a reference for farmers in selecting rice seeds. AHP is used in determining the weight of the criteria, while the TOPSIS method is used for ranking alternatives. The application of the AHP and TOPSIS methods was successfully implemented with the results of testing between systems with appropriate manual calculations and based on Black Box testing the system went according to design.</em></p><p><strong><em>Keywords:</em></strong><em> Decision Support System; Analytic Hierarchy Process; Technique for Order Performance by Similarity to Ideal Solution; Rice Seeds</em></p><p align="center"> </p><p align="center"><strong>Abstrak</strong></p><p>Banyaknya varietas padi menimbulkan permasalahan dalam pemilihan jenis varietas yang memiliki potensi untuk menghasilkan padi yang lebih banyak dan memiliki ketahanan terhadap hama dan penyakit. Salah satu cara untuk membantu pemilihan varietas padi yaitu dengan menggunakan sistem pendukung keputusan. Penelitian ini bertujuan mengimplementasikan metode <em>Analytic Hierarchy Process</em> (AHP) dan <em>Technique for Order Performance by Similarity to Ideal Solution</em> (TOPSIS) pada sistem pendukung keputusan untuk menentukan jenis padi yang lebih unggul berdasarkan alternatif yang ada sehingga dapat menjadi bahan acuan para petani dalam memilih bibit padi. AHP digunakan dalam penentuan bobot kriteria, sedangkan metode TOPSIS digunakan untuk perankingan alternatif. Penerapan metode AHP dan TOPSIS berhasil diterapkan dengan hasil pengujian antara sistem dengan perhitungan manual sesuai dan berdasar pengujian <em>Black Box</em> sistem berjalan sesuai dengan perancangan.</p><p><strong>Kata kunci</strong><strong>:</strong><em> Sistem Penunjang Keputusan; </em><em>Analytic Hierarchy Process; Technique for Order Performance by Similarity to Ideal Solution; Bibit Padi</em></p><p><strong><em> </em></strong></p>

The Selection of appropriate phase change material in the field of domestic water heating system is a difficult task due to the availability of the variety of an enormous number of different materials. The researcher’s primary objective is a selection of the desired PCM, which will give the best thermal performance of the domestic water heating latent heat storage system. The paper reports the selection of phase change material with three multi-criteria decision-making (MCDM) methods with conflicting and different objectives. An analytic hierarchy process (AHP) and entropy methods are used to determine the importance criteria weights. For selection purpose, the TOPSIS (Technique for order performance by similarity to ideal solution), VIKOR (Vise KriterijumskaOptimizacijaKompromisnoResenje), and EXPROM2 methods were used, which gives ranking to the alternatives using compromised weight obtained by AHP and entropy methods. This MCDM technique provides a list of all desirable options from the best to the worst suitable materials. Depending on the rankings obtained, the best PCM was found to be the Sodium acetate trihydrate (90%) + graphite (10%), Stearic acid and n-Hexacosane at the given criteria due to its higher physical, chemical, and thermal properties than other alternative PCM materials. The results obtained showed that these methods are feasible tool for the Selection of the best-suited phase change material and can be applied to any material selection decision-making problem to find the best materials.

This research aims to provide a novel approach for analysing road crash severity ranking by integrating all injury classified crash types. The road crash data of all Indian states (i.e., Andhrapradesh, Arunachal Pradesh, Bihar, etc.) for 2019 were incorporated to analyse severity rankings by using multi-criteria decision-making (MCDM) methods. Two of these methods – the Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to an Ideal Solution (TOPSIS) – were applied. The application of MCDM methods easily incorporated the injury classified crash data and provided clear rankings. Further, the correlation analysis of rankings provided by both MCDM methods proved the validity of the proposed research. Therefore, this approach is considered to have great potential to reform conventional severity ranking practices.

Sustainable material selection for additive manufacturing technologies: A critical analysis of rank reversal approach

The aim of this paper is to apply an integrated model, which combines methods of classical and fuzzy Multi-criteria decision making (MCDM) in selected six large equity companies from the Serbian energy sector. The data considered are retrieved from the official financial statements. Four main criteria were analyzed, identified by the previous researchers and pointing to the employees’ productivity: Operating income/Number of employees, Equity/Number of employees, Net income/Number of employees and Total assets/Number of employees. The contribution of this paper lies in the application of a hybrid model that integrates two MCDM methods: Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to analyse the employee productivity in selected D-Electrical power supply companies operating in Serbia. The FAHP is an effective method for mathematical representation of uncertain and imprecise evaluations made by humans, while the TOPSIS method is an efficient way to rank the alternatives. Results show that operating income is of highest importance for estimating employee productivity and decision making, while equity is of the weakest. Furthermore, the most productive operations in large enterprises from selected companies of the sector D-Electrical power supply are found in the company PC EPS Beograd, and the lowest are in the ED Center llc Kragujevac.

A new multi-criteria decision making approach based on wins in league to avoid rank reversal: A case study on prioritizing environmental deterioration strategies in arid urban areas

Technique for order performance by similarity to ideal solution (TOPSIS) is a Multi-Criteria DecisionMaking method (MCDM), that consists on handling real complex problems of decision-making. However, real MCDM problems often involve imperfect information such as uncertainty and inconsistency. The imperfect information is often manipulated through Neutrosophics theory, using certain degree of truth (T), falsity degree (F) and indeterminacy degree(I). and thus single-valued neutrosophic set (SVNs) had prodded a strong capacity to model such complex information. To overcome that kind of problems, In this paper, first, the authors simplify the popular TOPSIS method to a lite TOPSIS (S-TOPSIS), that gives the same result as standard version. Second, mapping STOPSIS to Neutrosophics Environment, investigating SVNS, called nS-TOPSIS, to deal with imperfect information in the real decision-making problems. Numerical examples show the contributions of proposed S-TOPSIS method to get the same results with standard TOPSIS with simple way of calculus, and how Neutrosophic environment manage the uncertain information using SVN

Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment

Manuscript type: Research paper Research aims: This study aims to identify evaluation criteria for e-commerce platforms and determine the top-performing platform in the Indonesian marketplace. Design/Methodology/Approach: The research employs a quantitative approach, utilising the Analytical Hierarchy Process (AHP) and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model analysis. It involves analysing data from 100 respondents who are users of Shopee, Tokopedia, and Bukalapak e-commerce platforms. Research findings: The findings suggest that the Usability criterion outperforms E-ServQual in terms of scores. Based on the AHP and TOPSIS techniques, Tokopedia, Shopee, and Bukalapak are ranked as the top three e-commerce platforms. Theoretical contribution/Originality: This study contributes to understanding the importance of usability in evaluating e-commerce platforms and provides insights into customer preferences. It also demonstrates the sequential integration of AHP and TOPSIS techniques for evaluating multiple criteria. Practitioner/Policy implications: This study reveals that Satisfaction, Efficiency, and Learnability are crucial sub-criteria for customers when selecting an e-commerce platform. Improving these aspects can enhance consumer purchasing power and improve the overall user experience. Research limitation/Implications: The limitation of the study is its geographic scope, as it was conducted solely in the Jakarta and Yogyakarta regions. Additionally, the research exclusively employs the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) methods.