Additive Ratio Assessment Method Research Articles

Multi-Criteria Decision Making Using Additive Ratio Assessment in Digital Voice Recorder Selection System

Digital Voice Recorder has many uses, usually used for interviews, recording voices and songs, recording meeting results, and can be used for learning. Currently, various Digital Voice Recorder products have been circulating and have different functions and specifications that are created according to the needs of users. For this reason, users must be observant in choosing a Digital Voice Recorder to support their work. So, we need a system that can provide recommendations and help in making decisions to choose the right Digital Voice Recorder. This study aims to develop a decision support system with Multiple Criteria Decision Making (MCDM) using Additive Ratio Assessment (ARAS) to assist in selecting a Digital Voice Recorder, so that it can assist in selecting the best solution appropriately and according to user needs. The ARAS method is used as a model that can select the best alternative based on the utility level of each alternative to determine the best alternative. Based on the case studies conducted, the utility values of each alternative were obtained, namely: Zoom Handy Recorder with a value of 0.5672, Sony PX470 with a value of 0.6147, Ruizu X52 with a value of 0.4664 and Tascam DR-22ML with a value of 0.9096. So, the best alternative is the Tascam DR-22ML. Based on testing through the black-box testing method, it shows that the system built has been running well

Penerapan Metode Additive Ratio Assesment (ARAS) Pada Sistem Pemilihan Tempat Kursus Bahasa Inggris Online

The selection of the right place for the online English course is certainly expected to produce output that is in line with expectations. For this reason, a solution is needed to help make decisions on choosing the right place for online English courses. A system that can assist in making decisions and can provide recommendations for the right choice is a decision support system (DSS). In the implementation of DSS, appropriate methods or models are also needed according to the cases discussed. One method that can be used is the Additive Ratio Assessment (ARAS) method. The ARAS method is a multi-criteria decision-making method based on the concept of classification using the utility level by comparing the overall index value of each alternative with the overall optimal alternative index value. The system created has features or functions that are in accordance with the needs of using the ARAS method in calculating to perform alternative rankings. Based on the case studies conducted, ARAS was able to find the best alternative from several alternatives with Lister results of 0.459, Engoo of 0.635, Golden English of 0.702, English Academy of 1. The system was made using the XP methodology, with features including being able to manage criteria values, alternatives and count to display the ranking of the best alternatives. In terms of functionality, the system that has been made has met expectations or in other words 100% functions well, and produces calculations that are in accordance with manual calculations. This system can be implemented in a choice of online English courses quickly and precisely.

Tribological Studies and Optimization of Two-Body Abrasive Wear of NaOH-Treated Vachellia Farnesiana Fiber by Additive Ratio Assessment Method

Tribological Studies and Optimization of Two-Body Abrasive Wear of NaOH-Treated Vachellia Farnesiana Fiber by Additive Ratio Assessment Method

Sustainable Circular Supplier Selection in the Power Battery Industry Using a Linguistic T-Spherical Fuzzy MAGDM Model Based on the Improved ARAS Method

In the power battery industry, the selection of an appropriate sustainable recycling supplier (SCS) is a significant topic in circular supply chain management. Evaluating and selecting a SCS for spent power batteries is considered a complex multi-attribute group decision-making (MAGDM) problem closely related to the environment, economy, and society. The linguistic T-spherical fuzzy (Lt-SF) set (Lt-SFS) is a combination of a linguistic term set and a T-spherical fuzzy set (T-SFS), which can accurately describe vague cognition of human and uncertain environments. Therefore, this article proposes a group decision-making methodology for a SCS selection based on the improved additive ratio assessment (ARAS) in the Lt-SFS context. This paper extends the Lt-SF generalized distance measure and defines the Lt-SF similarity measure. The Lt-SF Heronian mean (Lt-SFHM) operator and its weighted form (i.e., Lt-SFWHM) were developed. Subsequently, a new Lt-SF MAGDM model was constructed by integrating the LT-SFWHM operator, generalized distance measure, and ARAS method. In it, the expert weight on the attribute was determined based on the similarity measure, using the generalized distance measure to obtain the objective attribute weight and then the combined attribute weight. Finally, a real case of SCS selection in the power battery industry is presented for demonstration. The effectiveness and practicability of this method were verified through a sensitivity analysis and a comparative study with the existing methods.

METHODS COMPARISON OF ARAS AND TOPSIS FOR DETERMINING THE BEST PRACTICUM ASSISTANT (CASE STUDY CHEMICAL LABORATORY DEPARTMENT OF FMIPA UHO)

Practicum is one of the activities that are part of the curriculum in universities. The role of a practicum assistant is needed to support practicum activities. Practicum assistants is a selected through a selection process. The selection of practicum assistants at the Faculty of Mathematics dan Natural Science (FMIPA), Halu Oleo University, to be precise the department of Chemistry, is still done through a manual process. The problem faced in the selection process is that each lecturer determines the ranks of the selected practicum assistants sequentially, from the first practicum supervisor lecturer to the last, which takes a long time and subjective assessment is unavoidable. Then from that problem, it is necessary to develop a computerized system as a supporting media in decision-making to facilitate selecting practicum assistants. The Additive Ratio Assessment (ARAS) and Technique For Others Reference By Similarity To Ideal Solution (TOPSIS) method applicated to compare the results of the two ways. The results of the comparison of the two methods show that TOPSIS provides a higher accuracy value of 50%, while the accuracy value of the ARAS method is 44%, but from testing the speed of processing data, the ARAS method is faster than the TOPSIS method.

Optimization of atomized spray cutting fluid eco-friendly turning of Inconel 718 alloy using ARAS and CODAS methods

Atomized spray cutting fluid (ASCF) is a complex machining technology that results in increased productivity, improved surface quality, longer tool life, and cost savings. The purpose of this study is to investigate the effect of cutting process parameters on Inconel 718 alloy turning in dry and ASCF cutting environments. These two cooling environments’ essential machining indices, such as surface roughness, machining cost, power consumption, and tool life, were investigated. The cutting parameters were adjusted using desirability functional analysis, and two types of multicriteria decision-making (MCDM) methods were investigated: additive ratio assessment method (ARAS) and combinative distance-based assessment technique (CODAS). Both MCDM approaches yielded identical results, with the best settings being a cutting speed of 200 m/min, a feed rate of 0.08 mm/rev, and a depth of cut of 0.2 mm in an ASCF environment. ASCF machining considerably minimises the surface roughness, machining cost, power consumption and maximises the tool life by around 16%, 51%, 17%, and 48%, respectively, compared with dry machining.

Penerimaan Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode ARAS

Non-Cash Food Assistance (BPNT) is social food assistance that is paid in non-cash form every month by the government. However, the problem of identifying BPNT recipients has not been identified properly and it is not certain that the poor really deserve to receive BPNT. So far, the existing system has not been optimal for selecting BPNT recipients with the existing criteria. Data management still uses a manual system and is not effective in determining who is entitled to receive BPNT and who is not. A creative solution to overcome this problem is the use of a web-based decision support system (DSS) using the Additive Ratio Assessment (ARAS) method. A system based on human and computer intelligence that creates options to improve decision making. The purpose of this research is to develop a system that helps decision making in deciding the acceptance of BPNT in poor families. This makes it easy to determine who is eligible and who is not eligible for assistance. This method is easy to apply for ranking by comparing it with other methods so that the results are more precise and accurate. The calculation process for the ARAS method using a very complex web-based system greatly facilitates and speeds up the determination of BPNT receipts. To facilitate implementation, 10 data with 5 criteria were used as sample data. Based on the calculation results of the potential beneficiaries on behalf of Selamat and Prayogi, the priority is getting assistance with a final score of < 0.07.

A Sensitivity Analysis on a MCDM Problem Evaluated by ARAS Method

Multi-Criteria Decision Making, also known as MCDM, is a highly helpful technique for assessing numerous issues and conclusions as well as resolving conflicts in daily life. The choice of any technique, service, or product is fraught with difficulties. The choosing of any useful product, such as a scooter, is an important task that requires careful research into the selection criteria, where MCDM techniques play a significant role. But the results that are coming with different MCDM methods are has to be consistent enough. This particular study associated with the checking or verifying the results that are evaluated by the Additive Ratio Assessment (ARAS) method with AHP weights for each Criterion.

Fermatean fuzzy Heronian mean operators and MEREC‐based additive ratio assessment method: An application to food waste treatment technology selection

Uncertainty is often occurred in real-life decision-making problems due to the lack of complete information, imprecise data, and the vagueness of decision making experts in qualitative judgment, thus, the crisp values of criteria may be insufficient to handle such types of complex real situations. As the extension of fuzzy set, intuitionistic fuzzy set and Pythagorean fuzzy set, the Fermatean Fuzzy Set (FFS) has been demonstrated as a powerful tool to handle the uncertainty arisen in practical decision-making problems. Thus, this study aims to introduce an integrated Fermatean fuzzy information-based decision-making method by combining method based on the removal effects of criteria (MEREC) and additive ratio assessment (ARAS) methods with the application in a food waste treatment technology selection problem. By using Fermatean fuzzy numbers, the suggested approach successfully handle the qualitative data and uncertain information that often occur in practical situations. This study consists of four phases. First, entropy measure is developed for FFS and further utilized for determining the experts’ weights. Second, some Fermatean fuzzy Heronian mean operators and their properties are introduced to aggregate the Fermatean fuzzy information. These operators can provide us a valuable means to handle practical multicriteria decision-making problems on FFSs context. Third, an extended MEREC technique is originated to assess objective criteria weights within FFS context. Fourth, an integrated ARAS method is introduced with the combination of proposed entropy measure, generalized weighted Fermatean fuzzy Heronian mean operator and MEREC technique to evaluate and rank the alternatives. To confirm the reasonableness and practicality of the proposed methodology, an empirical case study of food waste treatment technology selection is discussed on FFSs settings. Further, a comparison with extant models and a sensitivity investigation are performed to confirm the validity and robustness of the obtained outcomes.

Sistem Pendukung Keputusan Pemilihan JSK di Ramayana Menerapkan Metode DEMATEL dan ARAS

JSK(Junior Supervisor cashier) is a person who has good experience, knowledge and skills to lead and manage finances every day. JSK also plays a role in regulating and coordinating cashiers on duty, starting from managing shifts, taking capital, and minimizing losses caused by cashiers. Decision Support System is a computer-based system consisting of several components, namely language system components, knowledge system components, and problem processing system components that are interrelated with one another, in making decisions through the use of data. -data and decision models in order to solve a problem. DEMATEL (Decision Making Trial And Evaluation Laboratory) aims to find direct (dependency) in a system of variables. The Additive Ratio Assessment (ARAS) method is a method used for ranking criteria, in carrying out the ranking process, the ARAS method has several steps that must be done to calculate and this method is very suitable for use in the selection of JSK candidates where the highest value is the best value of the final result

New entropy propositions for interval‐valued spherical fuzzy sets and their usage in an extension of ARAS (ARAS‐IVSFS)

AbstractThe spherical fuzzy set (SFS) concept and its interval‐valued version (IVSFS) are among the recent developments aiming at handling the hesitancy representation issue in multiple attribute decision‐making problems. In SFS, decision‐makers can assign independent membership, non‐membership, and hesitancy degrees. IVSFS extends this feature by assigning intervals to these three degrees. In this manner, the uncertainty, vagueness, and ambiguity hidden in human judgements can be quantified and processed more comprehensively. In multiple attribute decision‐making problems, the attribute weights are not commonly known. To determine these weights, there are two families of methods: subjective and objective ones. While subjective methods need expert judgements in weighting, objective methods can reveal the weights from the current dataset. Entropy‐based weighting technique is one of the well‐known objective methods. In the study, two IVSFS entropy expressions are introduced, and their practicality is presented in obtaining objective weights. Then, an IVSFS extension of Additive Ratio Assessment Method is proposed and integrated with the entropy‐based weighting schema. The proposition is applied in solving a 3D printer selection problem and a comparative analysis is conducted to check its robustness and validity.

Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study

Energy requirements have increased dramatically due to industrialization, economic, and population growth. To meet this demand, and solve its challenges, such as climate change, renewable energies do play an important role. This research work aims at selecting the best renewable energy projects using a hybrid decision-making framework from environmental, economic, technical, and social aspects at a sub-national level. In this regard, a new hybrid fuzzy multi-criteria decision-making model is deployed in which Vise Kriterijumska Optimizacija I Kompromisno Resenje, distance from average solution, and additive ratio assessment methods are used. In addition, for the weighing of criteria, Fuzzy Shannon’s entropy is used. Furthermore, the North Khorasan province is nominated as a sub-national study area. The results show that among 30 sub-criteria, social acceptance, net-presented cost, and noise were the top three with weights of 0.1105, 0.1003, and 0.0988, respectively. Solar energy projects also accomplished high ranks with an overall score of roughly 0.22. After that, small hydropower got second place with a score of 0.187. Moreover, the ranking of cities indicates that Jajarm was the most suitable location for implementing renewable energy development with a score of 0.14. Finally, sensitivity analysis was carried out to show that the mathematical model possessed good robustness.

A q-rung orthopair fuzzy ARAS method based on entropy and discrimination measures: an application of sustainable recycling partner selection.

The necessity and policy of eco-economy stimulate enterprises to attain sustainability by executing supply chain management. Generally, the evaluation process of sustainable recycling partner (SRP) selection is treated as a multi-criteria decision-making problem due to existence of numerous influencing aspects. To tackle the uncertain information during the process of SRP selection, the q-rung orthopair fuzzy sets have a good choice, which can refer to a broader range of uncertain decision-making information. Thus, this study presents a combined framework with the additive ratio assessment (ARAS) approach, notions of q-rung orthopair fuzzy set (q-ROFS) and information measures, and further implements to tackle the multi-criteria SRP selection problem with q-ROFSs setting. In this procedure, the criteria weights are evaluated with the integration of the subjective weights given by decision-experts and the objective weights obtain from the entropy and discrimination measures-based approach. For this, new entropy and discrimination measures are introduced for q-ROFSs and discussed the effectiveness of proposed measures. To elucidate the applicability of the present methodology, a case study related to sustainable recycling partner assessment is presented under q-ROFSs context. Sensitivity analysis is conducted over diverse set of criteria weights to verify the robustness of introduced framework. The results of the sensitivity analysis signify that the recycling partner SRP1 constantly secures the best rank and despites how sub-criteria weights differ. A comparison with extant methods is made to validate of the results of proposed one. The findings of the work verify that the developed framework is more valuable and well consistent with formerly proposed decision-making models.

A Hybrid MCDM Approach in Third-Party Logistics (3PL) Provider Selection

Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio assessment (ARAS) method to rank the alternatives from the best to the worst. The introduced hybrid–ARAS approach can be highly beneficial, since combining two methods gives more robust solutions on one hand, while on the other hand eliminating subjectivity. Comparative and sensitivity analyses showed the high reliability of the proposed hybrid–ARAS method. A hypothetical case study is presented to illustrate the potentials and applicability of the hybrid–ARAS method. The results showed that 3PL-2 was the best possible solution for our case.

Model for the Sustainable Material Selection by Applying Integrated Dempster-Shafer Evidence Theory and Additive Ratio Assessment (ARAS) Method

The construction industry is a vital part of the modern economic system. Construction work often has significant negative impacts on the environment and sustainable economic development, such as degradation of the environment, depletion of resources, and waste generation. Therefore, environmental concerns must be taken into account when evaluating and making decisions in the construction industry. In this regard, sustainable construction is considered as the best way to avoid resource depletion and address environmental concerns. Selection of sustainable building materials is an important strategy in sustainable construction that plays an important role in the design and construction phase of buildings. The assessment of experts is one of the most important steps in the material selection process, and their subjective judgment can lead to unpredictable uncertainty. The existing methods cannot effectively demonstrate and address uncertainty. This paper proposes an integrated Dempster-Shafer (DS) theory of evidence and the ARAS method for selecting sustainable materials under uncertainty. The Dempster-Shafer Evidence Theory is a relatively new and appropriate tool for substantiating decisions when information is nonspecific, ambiguous, or conflicting. The Additive Ratio Assessment (ARAS) method has many advantages to deal with MCDM problems with non-commensurable and even conflicting criteria and to obtain the priority of alternatives based on the utility function. The proposed method converts experts’ opinions into the basic probability assignments for real alternatives, which are suitable for DS evidence theory. It uses the ARAS method to obtain final estimation results. Finally, a real case study identifying the priority of using five possible alternative building materials demonstrates the usefulness of the proposed approach in addressing the challenges of sustainable construction. Four main criteria including economic, social, environmental, and technical criteria and 25 sub-criteria were considered for the selection of sustainable materials. The specific case study using the proposed method reveals that the weight of economic, socio-cultural, environmental, and technical criteria are equal to 0.327, 0.209, 0.241, and 0.221, respectively. Based on these results, economic and environmental criteria are determined as the most important criteria. The results of applying the proposed method reveal that aluminum siding with a final score of 0.538, clay brick with a score of 0.494, and stone façade with a final score of 0.482 are determined as the best alternatives in terms of sustainability.

Location assessment for producing biodiesel fuel from Jatropha Curcas in Iran

Biofuels are considered renewable sources of energy which can replace fossil fuels using naturally extracted fuels from the environment to fulfil growing demands for energy in developing countries. This paper aims to select a suitable province for producing biodiesel from Jatropha plants in new climate conditions of Iran using the additive ratio assessment method (ARAS). Previous feasibility studies lack the environmental factor when considering the cultivation of Jatropha plants in Iran. In this work, the relevant main selecting criteria were identified through using a literature review. Then, the most effective criteria were chosen and categorised as environmental, social and economical factors. The weighting of the criteria was determined by Shannon entropy method and using expert opinions. Next, the ARAS method was used for prioritizing the provinces in Iran. From the results, it is observed that the environmental factor is the key parameter for selecting biodiesel plant location. Furthermore, Golestan province was selected as the best candidate location in Iran for establishing a biodiesel plant using Jatropha plants. Using the semi-arid pastures of Golestan province (about 402,000 Hectares), 1,930,000 tons biodiesel can be produced annually for supplying the fuel to 600,000 diesel cars.

Additive Ratio Assessment (ARAS) Method for Selecting English Course Branch Locations

The research was conducted to overcome the problem of selecting a location for the opening of a new branch of the Murni Sadar English Course. The increasing need for the community to learn English has made Murni Sadar English Course to expand and open a branch of English courses in a new location. This problem is overcome by designing a support system that functions to help facilitate the selection of new branch locations. This DSS is designed using the Additive Ratio Assessment (ARAS) method using 5 criteria: population density level, access to locations, crowd level, rental costs, and population income. From the results of this study it is concluded that the ARAS method is very appropriate to be used as a tool in decision support where the best alternative location is Patuan_Anggi_Street with an alternative value of 0.1778.

Interval type-2 Fuzzy ARAS method for recycling facility location problems

The management of end-of-life vehicles (ELVs) is currently one of the most important ecological topics. The recycling process has essential importance for the environmental and economic sustainability of the ELV management. Istanbul has the highest rate of car ownership population in Turkey as well as an old vehicle fleet. There is a strong motivation to open an additional ELV recycling facility in this mega-city. Facility location is one of the crucial strategic problems for decision-makers. Addressing multi-criteria and highly uncertain nature of the ELV recycling facility location problem, this paper introduces a novel approach to support the facility location process. For the first time, an extension of the Additive ratio assessment (ARAS) method under the interval type-2 fuzzy environment is presented. The novel method is utilized for solving the ELV recycling facility location problem. The potentials and applicability of the presented interval type-2 fuzzy ARAS method are demonstrated throughout the real-life case study of Istanbul. The comparison with the available state-of-the-art interval type-2 fuzzy set based MCDM methods approves its validity and consistency.

Primena ARAS metode u evaluaciji efikasnosti osiguravajućih društava u Srbiji

The issue of assessment of the efficiency of insurance companies based on multi-criteria analysis has become increasingly pressing, complex and significant. It provides the grounds for the achievement of future improved efficiency of insurance companies by using adequate measures. With this in view, the paper analyses the efficiency of insurance companies in Serbia based on ARAS (Additive Ratio Assessment) method. The results obtained from the empirical research of the efficiency of insurance companies in Serbia by ARAS method show that the year 2020 was the most efficient. Lately, the efficiency of insurance companies in Serbia has continuously increased, positively triggered by a number of factors such as the economic climate, standard of living, employment, modern cost management concepts, revenues and profit, electronic sale of insurance services, digitization of overall business. The negative impact of the Corona virus pandemic in Serbia is negligible (compared to the other industries) and partially compensated for by the increased online sale of the insurance services and/or the growth in insurance of infrastructure (property) on the one hand and the raised awareness of the need to be covered by insurance against potential risks of all kinds, on the other hand.

A New Enhanced ARAS Method for Critical Path Selection of Engineering Projects with Interval Type-2 Fuzzy Sets

Appraising the alternative among a set versus conflicting factors is taken into account as an essential issue in real-world decision problems. In this paper, a new multicriteria group decision-making (MCGDM) model is introduced with a fuzzy relative preference relation (FRPR) concept and additive ratio assessment (ARAS) method. FRPR is a useful way to reduce time complexity and to avoid pairwise comparisons. Also, a new method for determining the weights of experts by using an extension of the reference point method is presented and added to this new MCGDM model for an aggregation of the experts’ judgments. Finally, a case study about the selection problem of the engineering project in exploration and sampling projects of lead and zinc mine by decisive criteria are solved to denote the capability of the presented model. Furthermore, to illustrate the various applications of the proposed method in different decision problems, an example of literature is solved.