Additive Ratio Assessment Method Research Articles

Sistem Pendukung Keputusan Seleksi Calon Karyawan Baru PT. Dawam Prima Perkasa Menggunakan Metode Aras Berbasis Web

Employees are one of the supporting factors for a company, because by having qualified employees, according to the qualifications and criteria needed by the company, then the company can develop and move forward in the future. No exception, PT. Dawam Prima Perkasa who is in need of new employees who are suitable to work in the company. However, PT. Dawam Prima Perkasa is faced with a problem where the large number of prospective employees who take the selection test will cause the number of incoming files to be adjusted to the criteria owned by the company and require a lot of time, making it prone to file errors. To minimize the occurrence of errors and the length of time used, a Decision Support System was created to determine the best prospective employees who will work in the company. The Decision Support System Method used is the Additive Ratio Assessment (ARAS). This research has gone through the process of validating the Spearman rank correlation and the value is 0.950. Based on these results, the ARAS method can be used in selecting prospective new employees at PT. Dawam prima Perkasa.

Wireless Sensors in Agriculture and Food Industry Using the ARAS Method

Wireless sensors in agriculture and food industry. Agriculture for Wi-Fi sensors and Wireless sensors in the food industry. Three styles of networks: big name community, hybrid community, and mesh network, developed and standardized Bluetooth technology Star networks use, such as beacons and scatterers are Each piconet is a primary node connects to seven slave nodes, whereas each Scatternet and more than one piconet Forms an ad-hoc network. Zigbee generation makes use of hybrid star networks, which use a couple of grasp Non-routing slave nodes Nodes with routing capabilities to connect. agricultural production and offer well-timed remarks to users. Nowadays, wireless sensor networks (WSN) are broadly utilized in agricultural monitoring to improve the satisfaction and productivity of agriculture. In this software, sensors collect various styles of statistics (ie, humidity, carbon dioxide stages, and temperature) in real-time shows. Stores, plant life, hospitals, parking plenty, or even eating places use wi-fi sensor networks (WSN) to improve patron experience, save emergencies, enhance delivery chains, and greater. Wireless sensors are used in the agricultural enterprise. Farmers can screen cattle. The sensors then gather data for evaluation. Therefore, ability threats such as diseases or animal feeding schedules are diagnosed through the tool to assist farmers to maintain their cattle healthy. A wi-fi sensor network is a radio frequency (RF) microcontroller and transceiver, Sensors, and machine made from strong sources. A wireless sensor with self-recovery capabilities Networks solves problems or traditional to allow programs that cannot be solved by technologies have improved. Once available, wireless sensor build is in its early development stage Many new programs not previously considered possible This technology allows us to detect Agriculture and wireless sensors in food establishments Applications are even rarer. Agriculture and Food A wireless sensor are suitable for industry This is an overview of the technology The article intends to present. The additive ratio assessment ARAS method for complex decision problems Tries to simplify and for alternatives that can reflect the difference between by the corresponding indicator (degree of use). Selects the "best" alternative. Radio, Data rate, Nodes per master, Slave enumeration latency, Data type, Range (m), Extendability, Battery life.Feature, WiFi (IEEE 802.11b), Bluetooth (IEEE 802.15.1), ZigBee (IEEE 802.15.4). Range (m) is showing the highest value of rank whereas Slave enumeration latency is showing the lowest value. Wireless sensors in agriculture and food industry for Additive Ratio Assessment method. Range (m) is showing the highest value of rank whereas Slave enumeration latency is showing the lowest value.

Identifying and Evaluating Businesses with Branding Potential in Rural Areas (Case study: Turkmen Sahara Region – Iran)

Purpose: In recent years, it has become more necessary to seek and apply new strategies to strengthen the foundations and diversification of economic activities in rural areas. Accordingly, in the context of the new theories of sustainable development, one of the approaches that is of great importance for the growth and sustainability of businesses in today's complex environments is branding. Therefore, the main purpose of this study was to identify businesses with branding potential in Turkmen Sahara of Golestan province in Iran. The overwhelming limitations of product marketing are supporting the declining revenues of traditional sources in dealing with competitive markets as well as trying to expand, making available and identifying regional products with a branding approach Design/methodology/approach: In this study, we first identified and localized the branding indices and then identified the brand-liable products in the region using the Additive Ratio Assessment (ARAS) method in multi-criteria decision making. Findings: The results showed that among the indicators of brand products in rural areas, satisfaction index with weight of 0.095 was put in the first place followed by adaptability with weight of 0.091, quality-orientation approach with a weight of 0.086 and valuable with a weight of 0.081. Also, among the common businesses and products in the region, cotton cultivation with a coefficient of 0.971 was the first priority followed by carpet weaving with a coefficient of 0.966, traditional foods with a coefficient of 0.952, Turkmen horse breeding with a coefficient of 0.943 and eco-tourism with a coefficient of 0.924 for planning the branding of products and services based on Brand Explanatory Indexes and using ARAS method. Practical implications: The study provides a perspective on the process of branding products and services in rural areas. Originality/value: This paper makes two major contributions: first, the introduction of branding indicators for rural businesses, and second, applying decision making models in the process of branding products and services with brand potential in rural studies.

Comparison of Multi Criteria Decision Making Methods SAW and ARAS: An Application to Performance of Indian Pharmaceutical Companies

While assessing the performances of companies, the decision makers to take not only a single criterion for making the right decisions in to account, but also a number of other relevant criteria that could affect the performance. Because when it is necessary to make the best selection among several option, Multiple-Criteria Decision Making (MCDM) methods are used. This study is to provide insight in to the applicability of method Simple Additive Weightings Method (SAW) and Additive Ratio Assessment (ARAS) method under MCDM techniques to evaluate the performance of Indian Pharmaceutical companies during the study period 2006-2019. The seventeen evaluation criteria’s were used in the application. The constructed model was analysed using both SAW and ARAS method. The study results showed that the best performance belongs to Glico Smith Kline Pharma Limited in SAW method and Sun Pharmaceutical Industries Ltd in ARAS method and worst performance belongs to Ranbaxy Laboratories Limited in both methods. By comparison, both methods revealed the similar rankings of companies during the study period.

Picture Fuzzy ARAS Method for Freight Distribution Concept Selection

Companies can perform their freight distribution in three different ways. The first concept, the in-house concept, represents the use of a company’s own resources and knowledge to organize transportation from the production to retailers or from the warehouse to customers. The opposite concept is to outsource distribution activities by hiring third-party logistics providers. The third concept represents a combination of the previous two. Although the arguments in favor of outsourcing can be found in the literature, an appropriate selection of a freight distribution concept is specific for each company and depends on many evaluation criteria and their symmetrical roles. This paper presents a methodology that can be used by companies that need to choose their freight distribution concept. An advanced extension of the Additive Ratio ASsessment (ARAS) method is developed to solve the freight distribution concept selection problem. To illustrate the implementation of the proposed methodology, a tire manufacturing company from the Czech Republic is taken as a case study. However, the proposed picture fuzzy ARAS method is general and can be used by any other company. To validate the novel picture fuzzy ARAS method, a comparative analysis with the nine existing state-of-the-art picture fuzzy multi-criteria decision-making methods is provided.

Development of a firm export performance measurement model using a hybrid multi-attribute decision-making method

PurposeThe present study is aimed to develop a firm export performance measurement model. Increased levels of globalization are forcing firms, especially SMEs (i.e. small and medium-sized enterprises) and entrepreneurial firms, to enter new markets and increase their exports. Consequently, export performance measurement has become a vital tool for achieving competitive advantages, and this type of measurement is considered an important topic of research in the field of international marketing. However, the literature lacks a comprehensive framework for measuring export performance, even though many criteria for gauging this performance's parameters have been discovered and applied.Design/methodology/approachA literature review was conducted, and the most important criteria for export performance measurement was identified using weights obtained by stepwise weight assessment ratio analysis method. Then, the export performance of five firms was evaluated using the additive ratio assessment method with interval-valued triangular fuzzy numbers.FindingsThe 15 most significant criteria were identified and categorized into three dimensions: economic, strategic, and other. The strategic dimension was identified as the most important, while the criteria “strategic goals achievement” and “return on investment” were found to be the most relevant.Practical implicationsA comprehensive framework including a definitive set of the most prominent, useful evaluation criteria was established which enables both scholars and practitioners to assess export performance.Originality/valueThe current study attempts to fill the gaps in the literature by presenting a comprehensive framework for export performance measurement.

Comparison of the ELECTRE, SMART and ARAS Methods in Determining Priority for Post-Natural Disaster RENAKSI Priorities

Each organization must collect data as a result of the use of information technology. Over time the data is processed into information. The information collected is used as a basis for decision making. But not all information can be directly used for the decision making process. Necessary methods and weighting in the process of getting information. One model in a decision support system is Multi Criteria Decision Making (MCDM). The MCDM model makes it possible to provide the best choice of information from several choices of the many criteria and alternatives used. This study compares the MCDM model, namely the ELECTRE (Elimination Et Choix Traduisant la Realite) method, SMART (Simple Multi-Attribute Rating Technique), ARAS (Additive Ratio Assessment) as a priority determination for the handling of areas affected by natural disasters which must be addressed first in the RENAKSI (Reconstruction and Rehabilitation Action Planning), in this case earthquake natural disasters. The ELECTRE method has a different algorithmic process than SMART and ARAS. The validation test method ELECTRE, SMART and ARAS against dataset occurrence of the earthquake is become the results of this research. Spearman rank correlation values ​​for the three methods amounted to 0.96. And another correlation method value of 0.85 for the ARAS method and 0.82 for the ELECTRE and SMART methods.

Resilient supplier selection to mitigate uncertainty: soft-computing approach

PurposeIn recent years, determining the effective and suitable supplier in the supply chain management (SCM) has become a key strategic consideration to the success of any manufacturing organization in terms of business intelligence (BI), as many quantitative and qualitative critical factors are measured from big data. In today’s competitive business scenario, the main purpose of this study is to determine suitable and sustainable suppliers during supplier selection process is to reduce the risk of investment along with maximize overall value to the customer and develop closeness and long-term relationships between customers and suppliers to build a resilient SCM to mitigate uncertainty for automotive organizations.Design/methodology/approachAs these types of decisions generally involve more than a few criteria and often necessary to compromise among possibly conflicting factors, the multiple-criteria decision-making becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, the aim of this paper is the presentation of a new integrated fuzzy analytic hierarchy process and fuzzy additive ratio assessment method with fuzzy entropy using linguistic values to solve the supplier selection problem to build the resilient SCM under uncertain data. Fuzzy entropy is used to obtain the entropy weights of the criteria.FindingsOrganizations gather massive amounts of information known as BD on the basis of historical records of uncertainties from several internal and external sources to manage uncertainty to improve the overall performance of organizations using BI strategy for analyzing and making effective decision to support the managements of automotive manufacturing organizations in an information system.Research limitations/implicationsAlthough this study tries to represent a full analysis on suitable and resilient global supplier selection under various types of uncertainty, still there are some improvements that can be made in the future by developing a more refined and more sophisticated approach to further enhance the performance of the proposed scheme to calculate overall rating scores of the alternatives.Originality/valueThe novelty of this paper is to propose a framework of BI in SCM to determine a suitable and resilient global supplier where all the meaningful information, relevant knowledge and visualization retrieved by analyzing the huge and complex set of data or data streams, i.e. BD based on decision-making, to develop any manufacturing organizational performance worldwide.

Selection of eco-friendly cities in Turkey via a hybrid hesitant fuzzy decision making approach

Environmental pollution can be defined as the alteration and deterioration of the natural structure and composition of the environment. Industrialization and population density in cities increase environmental pollution. Today, environmental pollution, a common problem in all countries, has reached dimensions that threaten nature and human health. In this context, this study focuses on the selection of eco-friendly cities in Turkey according to criteria such as average PM10 values at air quality measurement stations, forest area per km2, and percentage of population receiving waste services, using the hesitant fuzzy linguistic term set (HFLTS)-based additive ratio assessment (ARAS) method. The multi-criteria HFLTS method is used to determine the weights assigned to environmental criteria. The ARAS method is used to obtain the final ranking of 81 cities in Turkey. Empirical results demonstrate that the proposed approach is viable in selecting eco-friendly cities.

An Extension of ARAS Methodology for Multi-criteria Group Decision-Making Problems within Probability Multi-valued Neutrosophic Sets

Probability multi-valued neutrosophic sets (PMVNSs) can depict the preference and hesitancy of decision makers (DMs) simultaneously, and utility-based additive ratio assessment (ARAS) can effectively evaluate and rank feasible alternatives. In order to make optimal decision making under the environment of the PMVNSs, in this paper, an extended ARAS methodology for multi-criteria group decision making (MCGDM) is developed. Firstly, we propose probability multi-valued neutrosophic normalized weighted Bonferroni distance (PMVNNWBD) to measure the closeness of weighted probability multi-valued neutrosophic numbers (PMVNNs). Then, an entropy measure for PMVNSs is proposed to describe the inaccuracy degree of PMVNSs and to derive the weights of DMs. Further, considering the relationship between criteria, we construct a modified maximizing deviation model based on PMVNNWBD to obtain criteria weights. Moreover, an extended ARAS method for MCGDM is established to handle PMVNSs based on the obtained weight information of DMs and criteria. Finally, the feasibility and superiority of the proposed approach are verified by a case study concerning third-party logistics (3PLs) supplier selection, and sensitive analysis of different parameters shows our proposed approach is flexible.

INTEGRATING BWM AND ARAS UNDER HESITANT LINGUISTIC ENVIRONMENT FOR DIGITAL SUPPLY CHAIN FINANCE SUPPLIER SECTION

In the era of intelligence and informatization, digital supply chain finance (DSCF) has become one of the important trends in the development of supply chain finance. With the gradual increase of DSCF suppliers and various requirements of small and medium-sized enterprises for suppliers in providing financing services, selecting the most suitable DSCF supplier is of great significance for most small and medium-sized enterprises to expand reproduction and improve competitiveness. To address such a decision-making problem, this paper proposes a new multi-expert multiple criteria decision-making model by integrating the Best Worst Method (BWM) and Additive Ratio ASsessment (ARAS) method under the hesitant fuzzy linguistic environment, in which the hesitant fuzzy linguistic BWM method is applied to determine the weights of criteria while the hesitant fuzzy linguistic ARAS method is proposed to rank the candidate suppliers. A case study is given to demonstrate the procedure of the proposed method for the selection of optimal DSCF suppliers, which shows the feasibility of the proposed method. Finally, sensitivity analysis and comparative analyses are provided to testify the applicability and superiority of the proposed method.

Evaluating the human performance factors of air traffic control in Thailand using Fuzzy Multi Criteria Decision Making method

The paper aims to identify and evaluate the factors influencing the human performance of Air Traffic Control (ATC) in Thailand. The objective of the study has been operationalized utilizing the extended SHEL model of ergonomics. Fuzzy Graded Mean Integration method has been employed to establish the importance and Fuzzy Additive Ratio Assessment method was utilized to measure actual performance of the factors on the response received from all ten air traffic control centers of Thailand. The finding of study facilitates the insights for improvement of various dimensions and constructs for an effective human performance management for ATC in Thailand. The study fulfills the theoretical gap by employing the Fuzzy Multi Criteria Decision Making (MCDM) method of identifying and measuring human performance in ATC.

Decision Support System For The Selection Of The Best Extension Officers Applying The Method Of Additive Ratio Assessment (Case Study: Department Of Agriculture Deli Serdang)

Agricultural extension workers are agents of change directly related to farmers. The selection of instructors so far that takes place at the Deli Serdang Agriculture Office takes a very long process, based on the problem, a decision support system (SPK) is needed that can facilitate the selection of the best instructors by using existing criteria. One method used is Additive Ratio Assessment (ARAS). The ARAS method is able to solve problems in decision making with alternatives and criteria that have been given weight. Research using ARAS ranks the lowest extension to the highest ranking. The best instructor selection system was built using Microsoft Visual Studio 2008 and MySQL as a database.

Optimisation of EDM process parameters for AA7050-10 (WT) % B<SUB align="right">4C composite through ARAS, grey and Taguchi technique

The present paper discusses the development of AA7050-10(wt.) % B4C composite through flux assisted stir casting method and its machinability using die sinking EDM. Taguchi L16 orthogonal array were used to perform experiments. Material removal rate, surface roughness and tool wear rate were evaluated as machinability measure by considering the concurrent effect of various process parameters. The collected responses were optimised using additive ratio assessment (ARAS) and grey relation analysis and Taguchi technique. Pulse current of 16 A, pulse on time of 200 μs, and pulse off time of 30 μs were obtained as the optimum machining parameters. The validity of the Taguchi analysis was further verified by conducting a confirmation experiment. The error estimation for both methods is less than 5%. However, ARAS method gives the least percentage error than grey relation analysis. Hence, ARAS model is suitable to optimise the process parameters of electro discharge machining.

Machinery/Service system Scheduled Replacement time determination: A combine Weighted Aggregated Sum Product Assessment, Additive Ratio Assessment and Age Replacement Model approach

The productivity of manufacturing/service industries greatly depend on the safety and reliability of the machinery/service system use for production/service delivery. The safety and reliability of the system can only be guaranteed through efficient maintenance. Scheduled replacement is an integral element of maintenance strategies. The major challenge of the maintenance policy is the determination of the optimum interval for carrying out replacement of equipment item of machinery/service system. A number of approaches have been applied in the literature in addressing this problem but these techniques have one limitation or another. In this paper, an MCDM approaches which avoid these limitations is proposed. The proposed Multi-Criteria Decision Making (MCDM) techniques combined weighted Aggregated Sum Product Assessment (WASPAS) and Additive Ratio Assessment (ARAS) with Age Replacement Model (ARM) for the determination optimum scheduled replacement time interval. The ARM for cost, reliability and downtime are aggregated using WASPAS and ARAS methods in order to rank alternative time intervals. The WASPAS and ARAS methods outputs are compared with another well-known technique in literature. To demonstrate the applicability of the proposed approaches a numerical example was applied. The result of the analysis revealed that, WASPAS and ARAS produces similar ranking for alternatives when compared with that of TOPSIS technique in the literature which is more computationally intensive, thereby validating the suitability of the proposed approaches. Keyword: Scheduled Replacement interval, WASPAS, ARAS, Age Replacement Model, decision criteria

Machinery/Service system Scheduled Replacement time determination: A combine Weighted Aggregated Sum Product Assessment, Additive Ratio Assessment and Age Replacement Model approach

The productivity of manufacturing/service industries greatly depend on the safety and reliability of the machinery/service system use for production/service delivery. The safety and reliability of the system can only be guaranteed through efficient maintenance. Scheduled replacement is an integral element of maintenance strategies. The major challenge of the maintenance policy is the determination of the optimum interval for carrying out replacement of equipment item of machinery/service system. A number of approaches have been applied in the literature in addressing this problem but these techniques have one limitation or another. In this paper, an MCDM approaches which avoid these limitations is proposed. The proposed Multi-Criteria Decision Making (MCDM) techniques combined weighted Aggregated Sum Product Assessment (WASPAS) and Additive Ratio Assessment (ARAS) with Age Replacement Model (ARM) for the determination optimum scheduled replacement time interval. The ARM for cost, reliability and downtime are aggregated using WASPAS and ARAS methods in order to rank alternative time intervals. The WASPAS and ARAS methods outputs are compared with another well-known technique in literature. To demonstrate the applicability of the proposed approaches a numerical example was applied. The result of the analysis revealed that, WASPAS and ARAS produces similar ranking for alternatives when compared with that of TOPSIS technique in the literature which is more computationally intensive, thereby validating the suitability of the proposed approaches.

Subcontractor selection with additive ratio assessment method

Subcontractor selection with additive ratio assessment method

AN INTEGRATED FUZZY AHP AND ARAS MODEL TO EVALUATE MOBILE BANKING SERVICES

Mobile banking (M-banking) which integrates software, hardware, and human is a new platform for banks. Determining the performance of M-banking services helps bank practitioners identify better policy to improve their positions. The aim of this study is to develop an integrated model for evaluating M-banking services by two methods, namely the Fuzzy Analytic Hierarchy Process (FAHP) with an extent analysis approach and ARAS (Additive Ratio ASsessment). In this study, the priority weights obtained through the FAHP are combined with the ARAS method to as­sess and rank the M-banking services. Moreover, in order to verify the applicability of this proposed model, a case study in Turkey is offered. The findings indicate that facilitating conditions play the most determining role in the adoption of the M-banking, followed by self-efficacy, privacy risk, and security risk. Consequently, the proposed model helps to overcome difficulties in M-banking service evaluation process and increases the efficiency of the M-banking service activities. Besides, the case study validates that the proposed model is an effective and efficient decision making tool for the evaluation of M-banking services under fuzzy environments.

A combination mathematical model (FA, AHP, FARAS) for ranking the effective factors on strategic outsourcing in supply chain of small and medium manufacturing enterprises

Outsourcing is one of the most popular business strategy in the global era. Outsourcing can bring tremendous benefits to organisations, but if an outsourcing decision is not precise and factors influencing the outsourcing decision are not considered, it can also bring irreparable damage. This study is to identify and rank the factors affecting the outsourcing on the basis of strategic perspective in supply chains of small and medium manufacturing enterprises. In this study, the factors influencing the strategic outsourcing decisions were determined on the basis of prior literature. In this approach, the refinement of the parameters using factor analysis was conducted to determine the most important sub-indices, and then due to the multidimensional nature of these factors, the analytic hierarchy process technique used for the weighting of factors and fuzzy additive ratio assessment method are used for ranking sub-criteria factors influencing strategic outsourcing. The findings show that the 'quality' is the most important factor and 'management agent' is the factor with the lowest importance.

Multi-criteria analysis of electricity generation technologies in Lithuania

The paper presents the process of choice of electricity generation technologies, which has been solved using a case of Lithuania's power sector and such multiple criteria mathematical methods as AHP (Analytic Hierarchy Process) and ARAS (Additive Ratio Assessment method). Having considered the impact of environment, a set of evaluation criteria was compiled for electricity generation technologies. Analysis of qualitative and quantitative criteria helped to rate the electricity generation technologies considering their economic, technological, environmental social and political aspects and rank them in order of priority. The derived results show that in case of Lithuania it is viable to consider further development of the nuclear power generation capacity. Among the electricity generation technologies related to renewable energy sources a clear priority is assigned to biomass technologies. Sensitivity analysis performed by applying multi criteria method ARAS, has confirmed this result.