Multi-Criteria Analysis in the Decision-Making Approach for the Linear Ordering of Urban Transport Based on TOPSIS Technique

The effects of urban transport are highly concerning. The rapid urbanization and motorization in smart cities have a huge impact on sustainability. The goal of the paper is to analyse the smart cities selected, in terms of the urban transport. This paper presents an overview of research works published between 1991 and 2020 concerning urban transport and MCDM (multi-criteria decision making). The author highlights the importance of decision-making criteria and their weight, as well as techniques. Seven criteria and forty-four objects were used as the input of the approach. The entropy weight method was used to compute the weight of each criterion. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was applied to calculate the assessment and ranking of transport performance for each smart city. Portland was found to be the best location for transport enterprises and projects; Tbilisi was ranked last. The values of the relative closeness coefficient ranged from 0.03504 to 0.921402. Finally, some suggestions for future research are discussed.

Sustainable performance analysis and ranking of organizations through fuzzy multi-criteria group decision making - A case study

In this paper, a decision support methodology for multiple attributes group decision making problem is developed. The proposed methodologies are based on Data Envelopment Analysis (DEA), Grey Relation analysis (GRA) and hybrid GRA-DEA methods. These methods are implemented for evaluation and ranking of organizations in sustainable perspective. In the proposed methods, the payoff values of alternatives are expressed in linguistic terms, given by the decision makers. Then, these linguistic terms are described by triangular fuzzy numbers. Charnes model of DEA is formulated in fuzzy environment to determine efficiencies of DMUs. Following the GRA method’s algorithm, a relative closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distances to the fuzzy positive-ideal solution (FPIS), as well as to the fuzzy negative-ideal solution (FNIS). Also, performance evaluation of these companies is made through hybrid GRA-DEA in fuzzy environment. The weights of the criteria are determined objectively during evaluation of these companies in the proposed GRA and DEA-GRA methods. Comparison of proposed approaches is made and final ranking of the organizations is sustainable perspective is arrived. The proposed methodologies are illustrated with a case study of five steel manufacturing companies in India.

Evaluation of automobile parts design scheme for intelligent manufacturing

Aiming at the selection of modern auto parts design schemes, an evaluation method of automobile parts design scheme for intelligent manufacturing is proposed. Considered the environment-friendly factors and traditional manufacturing factors, the evaluation index system of automobile parts design scheme was established, which taken technology, environment, economy and quality reliability as the first level evaluation index, and 12 second level indexes under the first level index. The game theory method was used to comprehensively consider the proportion of subjective and objective weights to determine the composite weight of each index. Aimed at the certainty and uncertainty of the evaluation index, the set pair analysis relative closeness method was used to calculate the composite weight and established the model. Three sets of automobile panel design schemes of a company were selected, and the mathematical model was used to calculate them. With the help of C language program, the advantages and disadvantages of the three design schemes were evaluated, and the optimal scheme was obtained. The calculation example proves that the method is true and effective, conforms to the background of modern intelligent manufacturing, and the calculation is simple, and has good feasibility and practicability.

Hesitant Fuzzy 2-Dimension Linguistic Programming Technique for Multidimensional Analysis of Preference for Multicriteria Group Decision Making

The hesitant fuzzy 2-dimension linguistic element (HF2DLE) allows decision makers to express the importance or reliability of each term included in a hesitant fuzzy linguistic element as a linguistic term. This paper investigates a programming technique for multidimensional analysis of preference for hesitant fuzzy 2-dimension linguistic multicriteria group decision making. Considering the flexibility of HF2DLEs in expressing hesitant qualitative preference information, we first adopt HF2DLEs to depict both the evaluation values of alternatives and the truth degrees of alternative comparisons. To calculate the relative closeness degrees (RCDs) of alternatives, the Euclidean distances between HF2DLEs are defined. Based on RCDs and preference relations on alternatives, the group consistency and inconsistency indices are constructed, and a bi-objective hesitant fuzzy 2-dimension linguistic programming model is established to derive the criteria weights and positive and negative ideal solutions. Since the objective functions and partial constraint coefficients of the established model are HF2DLEs, an effective solution is developed, through which the RCDs can be calculated to obtain the individual rankings of alternatives. Furthermore, a single-objective assignment model is constructed to determine the best alternative. Finally, a case study is conducted to illustrate the feasibility of the proposed method, and its effectiveness is demonstrated by comparison analyses.

Application of TOPSIS Method for Prediction of Optimum Design Parameters of Micro Hole Textured Cutting Inserts in Turning of Al-MMC

Metal Matrix Composite (MMC) has better mechanical properties and it is possible to produce near net shape. Aluminum-based MMC (Al-MMC) has challenges in terms of machinability studies and estimation of its optimum process parameters. Alternative cutting fluid research is a challenging area in machining. To avoid, existing hydrocarbon oil-based cutting fluid, textured inserts embedded with a solid lubricant are one of the alternative solutions. Micro hole textured inserts make a hole on the rake face of the cutting tool inserts. Texture includes various important design parameters namely hole diameter, hole depth and pitch between the holes. These optimum parameters influence the machining process. In this work, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to find the optimum design parameters (hole diameter, hole depth and pitch between holes) during turning of Al- MMC. The objective parameters considered are minimization of surface roughness, power consumption and tool flank wear. The optimum combination of these design parameters is obtained by the higher relative closeness value of the TOPSIS method. The result of the investigation revealed that these design parameters are important to obtain improved machining performance. Also, it is understood that the TOPSIS method has an appropriate procedure to solve multiple objective optimization problems in manufacturing industries.

TOPSIS Hybrid Multiattribute Group Decision-Making Based on Interval Pythagorean Fuzzy Numbers

Aiming at the mixed multiattribute group decision-making problem of interval Pythagorean fuzzy numbers, a weighted average (WA) operator model based on interval Pythagorean fuzzy sets is constructed. Furthermore, a decision-making method based on the technique for order preference by similarity to ideal solution (TOPSIS) method with interval Pythagorean fuzzy numbers is proposed. First, based on the completely unknown weights of decision-makers and attributes, interval Pythagorean fuzzy numbers are applied to TOPSIS group decision-making. Second, the interval Pythagorean fuzzy number WA operator is used to synthesize the evaluation matrices of multiple decision-makers into a comprehensive evaluation matrix, and the relative closeness of each scheme is calculated based on the TOPSIS decision-making method. Finally, an example is given to illustrate the rationality and effectiveness of the proposed method.

Penerapan Metode Topsis Untuk Pemilihan Vendor Terbaik

The selection of vendors to work on a project is an activity that must be carried out effectively and precisely so that the project is carried out in accordance with business needs and does not suffer losses. To get the best vendor ranking, you can use the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) calculation method. TOPSIS method is a method that generates rankings by calculating the distance between the best solution and the worst solution. The steps to calculate using TOPSIS are identification of alternatives and their values, create a decision matrix, normalize the matrix, calculate the normalization matrix, look for positive and negative solutions, calculate the distance between positive and negative solutions, and calculate relative closeness and sort preferences. In this study using 8 criteria and 5 alternative vendors. Research method using research and development. This method will produce a prototype. The results of the calculation of TOPSIS obtained vendor c who gets the highest score and vendor b with the lowest rank

Spare Parts Supplier Selection Design: A Case Study of A Railway Company

Spare parts support is essential for rolling stock maintenance management. The current supplier selection model determines the selected supplier based on evaluating one aspect of the criteria (product aspect). The selection of suppliers with poor performance occurred between 2018-2020 related to the delivery of goods that exceeded the deadline and goods that did not meet specifications. The first objective of this research is to analyze and determine the relevant priority criteria for selecting suppliers of rolling stock spare parts for railway companies. The second objective is to determine the rolling stock spare parts supplier by using the evaluation criteria determined in the previous process. The method used in this research is the integration of the Fuzzy Delphi Method (FDM), Analytical Hierarchy Process (AHP), and Technique for Others Preference by Similarity to Ideal Solutions (TOPSIS). FDM is used to select important criteria for the selection of suppliers of rolling stock parts. AHP is used to assist in choosing various criteria through evaluation in determining the criteria's weight. TOPSIS is used to assess supplier ratings. A total of 13 criteria from 19 alternative criteria have been selected for railway companies, especially in selecting rolling stock spare parts suppliers. Furthermore, the selection becomes the basis for bidding. Finally, Supplier A is the supplier with the highest relative closeness value (0.591), followed by Supplier B (0.545), and the lowest is Supplier C (0.282).

Utilization of Renewable Energy Sources in Road Transport in EU Countries—TOPSIS Results

The primary aim of this study was to assess and compare EU countries in terms of the use of renewable energy sources in road transport. The following research tasks were undertaken to realize this aim: (1) a review of the literature concerning the negative externalities in road transport, the concept of sustainable development, and legal regulations referring to the utilization of renewable energy sources; (2) presentation of changes in energy consumption (both traditional and renewable) in road transport in EU countries in the years 2008–2019; and (3) identification of leaders among the EU countries in terms of consumption of renewable energy sources in road transport. The aim and tasks were realized using the literature review and TOPSIS method as well as descriptive, tabular, and graphic methods. The analysis was conducted for 28 EU countries according to the status for 2019. The period of 2008–2019 was investigated. Sources of materials included literature on the subject and Eurostat data. Although renewable energy sources accounted for as little as 6% of total energy consumption in road transport in EU countries in 2019, this is a significant topical issue. It results from the direction in which changes need to be implemented in terms of energy generation in this area of human activity. It turned out that blended biodiesel and blended biogasoline were the most commonly used fuels originating from renewable sources. The application of the TOPSIS method resulted in the identification of five groups of EU member countries, which differed in terms of the degree of utilization of renewable energy sources in road transport. Luxemburg, Sweden, and Austria were leaders in this respect. In turn, Malta, Estonia, and Croatia were characterized by very low consumption of renewable energy. The greatest progress in the utilization of renewable energy sources in road transport was recorded in Sweden, Finland, and Bulgaria (changes in the relative closeness to the ideal solution from 0.15 to 0.27), while the greatest reduction in relation to other countries was observed in Austria, Germany, and Lithuania (changes from −0.35 to −0.22).

Evaluation of Vehicle Handling Stability Based on Interval TOPSIS and Entropy Weights

The purpose of this study is to evaluate the handling stability of vehicle from the perspective of users using a multi-criteria decision-making approach with interval numbers. In order to achieve this purpose, the evaluation criteria easy for drivers to understand were constructed based on questionnaire, the interval weights of the criteria were calculated using the entropy weight method with interval numbers, and the interval TOPSIS method was used to evaluate the vehicle handling stability. As the improvement of the method, a new method to determine the crisp value of the interval weight was given, and the relative closeness index used for ranking alternatives was extended to a new additive ranking index. The proposed method was used to evaluate the handling stability of 12 vehicles, and the results may provide some basis for vehicle R & D and design.