ORESTE Method Research Articles

Decision Support System Selecting The Best Skincare Using The Oreste Method

Decision Support System Selecting The Best Skincare Using The Oreste Method

An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method

An Evaluation of the logistics Performance Index Using the ENTROPY-based ORESTE Method

A Fermatean Fuzzy ORESTE Method For Evaluating The Resilience of the Food Supply Chain

To study the resilience and driving factors of key players in the food supply chain, this paper applies a decision model based on the Fermatean fuzzy set and improved ORESTE method. Firstly, based on the existing research on food supply chain resilience, the risk influencing factors affecting food supply chain resilience is established through a literature review. Secondly, Fermatean fuzzy sets are used to express and integrate uncertain information, calculate the membership and non-membership degrees of the factors affecting the resilience risk of the food supply chain, and then calculate the score function to obtain the weight of the influencing factors and the risk weight of alternatives. Finally, the improved ORESTE method is used to rank key players, thereby identifying key players in the food supply chain that affect resilience. The results show that transportation and logistics failures, government regulation, and diseases are the three important risk factors with the highest weight coefficient, while water system failure is the least important risk factor. Among the key players, farmers and food processors are considered the most vulnerable key players in the food supply chain, while the most resilient key players are supermarkets and food wholesalers.

Failure mode and effect analysis with ORESTE method under large group probabilistic free double hierarchy hesitant linguistic environment

Failure Mode and Effect Analysis (FMEA) is a prospective and systematic analytical tool widely used to improve the reliability and safety of various industries. However, the existing FMEA methods have received criticism for their inherent deficiencies that limit their flexibility and effectiveness. To address these issues, we propose a novel FMEA model that combines Probabilistic Free Double Hierarchy Hesitant Linguistic Term Set (PFDHHLTS), Extended Grey Relation Analysis (EGRA), and ORESTE to determine the priorities of Failure Modes (FMs). Firstly, the PFDHHLTSs are proposed to represent experts’ assessments, improving the flexibility and accuracy of experts’ expressions. Secondly, the PFDHHLTS-EGRA is proposed to determine the evaluation matrix and the weights of risk factors in a large group environment. Furthermore, the ORESTE method is extended to the PFDHHLTS environment. Lastly, we verify the effectiveness of our method through a case study on the aluminum electrolysis process. The results demonstrate the effectiveness and flexibility of our method in expressing experts’ assessments and obtaining more accurate and reliable risk priorities.

Implementation of the ORESTE Method in Determining the Selection of Service Ambassador Events

The selection of candidates to become Service Ambassadors is an important and complex process. Assessors need to consider many factors and the relative weight of each factor to ensure the best candidate is selected for the position. One method that can be used in candidate selection is the ORESTE method. The ORESTE method is a multi-criteria decision-making method developed by J.P. Brans and B. Mareschal in 1994. This method allows assessors to aggregate multiple criteria and consider the relative weight of each criterion to compare alternatives and produce a ranking of candidates based on the highest relative value. In the context of Service Ambassador selection, the ORESTE method can assist assessors in solving complex decision-making problems and ensuring the best candidate is selected for the position. The method allows raters to consider multiple criteria and consider the relative weight of each criterion, resulting in a ranking of candidates based on the highest relative value. Thus, the use of the ORESTE method in determining the selection of Tourism Ambassadors can simplify and speed up the candidate selection process, as well as increase accuracy and satisfaction in decision making. By using the ORESTE method, the results of the decision to select the winner of the Service Ambassador event are obtained with a preference value of 4.42

The Implementation of ORESTE using Basson Rank for Selecting The TOEFL Preparation Courses in Yogyakarta

TOEFL is one of the most frequently used international standardized tests for registering for masters and doctoral degrees, seeking study scholarships or for promotions. Unfortunately, there are still many students and employees who still experience difficulties in taking the TOEFL test. This is what then becomes the reason for them to take English courses, especially to prepare themselves for preparing the TOEFL test. Yogyakarta, which has the title of "Student City", has many campuses and many English courses that offer the TOEFL Preparation Course. There are many types of TOEFL formats and many TOEFL Preparation Programs are offered by English courses in Yoggyakarta. The TOEFL Preparation courses has various programs including different price, teacher competencies, and facilities. In this study, the ORESTE method was used to help the people determining the best course according to its ranking. This method is one of the Multiple Attribute Decision Making (MADM) methods used to find alternatives using predetermined criteria and preference weights. The criteria used are price, instructor, materials, facilities and location. The results showed that the best TOEFL course ranking/order alternative was A16 with a preference score of 3.9425 and the course with the lowest score was A4 with a score of 9.878177.

An Application Of Satisfaction Assessment Of Community Services In Padang Lebar Village Office Using The Oreste Method

The process of assessing community satisfaction in Padang Lebar Village Office manually is by using a questionnaire, therefore an application was made to facilitate the assessment of satisfaction with these community services. The application for assessing satisfaction with community services is an application used to assess community satisfaction with the services provided by employees of Padang Lebar Village Office. The research method used is the Oreste Method, which is a multi-criteria decision making method or better known as Multi Criteria Decision Making (MCDM). MCDM is used to solve problems with conflicting criteria to be able to make a decision to reach a final decision. The result of this research is a software that adopts the Oreste method which is able to help Padang Lebar Village Office for decision making in determining the level of service satisfaction to the community every year. This application for assessing satisfaction with community services can help the management of Padang Lebar Village Office in assessing the performance of village employees. The Writer suggests that the application for assessing satisfaction with community services can be used to facilitate inputting data in assessing community satisfaction with existing services at the Padang Lebar Village Office.

Correction: Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings

Correction: Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings

Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings

As an important major public health emergency, COVID-19 broke out more than two years. At present, China has entered the post-epidemic era. However, it is still necessary to study the medical health resource allocation in public health emergencies. Therefore, the evaluation of medical health resources allocation is important. Firstly, we use two kinds of linguistic preference orderings (LPOs) to represent experts’ opinions when evaluating the medical health resources allocation in public health emergencies. Then, a novel ORESTE method with LPOs is developed to solve multiple criteria decision-making (MCDM) problems. Additionally, we apply the proposed ORESTE method to solve a practical MCDM problem involving the medical health resources allocation in public health emergencies. Finally, some comparative analyses among the proposed ORESTE method and some existing methods under a double hierarchy linguistic environment are set up, and some discussions are summarized to show the validity and applicability of the proposed novel ORESTE method.

PEMILIHAN JENIS BIBIT UNGGUL TANAMAN NANAS DENGAN METODE ORESTE

Indonesia is a country that has a tropical climate that is rich in fruits. One of the tropical fruit commodities in Indonesia is pineapple. Pineapple is most interest by public because price of the fruit is cheap, easy to obtain and has a distinctive aroma, taste, and color. Pineapple can be used as a medicinal plant. In the cultivation of pineapple plants, require the availability of good land and availability of seedlings that can be obtained in a vegetative and generative methods. Pineapple seeds obtained by generative means are fruit crowns, tiller shoots, root shoots, fruit shoots, stem cuttings. Meanwhile, pineapple seeds obtained by generative means are pineapple seeds. In pineapple cultivation carried out by pineapple farmers in Panribuan Village, Simalungun Regency, it is still based on farmer’s instincts and feelings, so that pineapple harvests often occur that are less than optimal, are not resistant to pests, yields are less than optimal, harvest age becomes longer. With the alternatives that exist in the decision support system with the ORESTE method to select superior seeds of pineapple plants. A decision support system is one of the ways to organizing information intended to be used in decisions making. ORESTE is a method that was built for conditions where a set of alternatives will be sorted by criteria according to the levels of importance. From the calculation results obtained the best alternative is sapling shoots with the preference value of 1,547

An interval type-2 fuzzy ORESTE method for waste-to-energy plant site selection: A case study in China

Serving as a promising solution to manage municipal solid waste (MSW), the waste-to-energy (WTE) system has recently received increasing attention. The first and critical step of constructing a WTE system is selecting a sustainable plant site. To support the site selection of the WTE system, this paper proposes a novel interval type-2 fuzzy decision-making framework. First, a sustainable evaluation index system is established by considering multiple criteria from several dimensions. Second, to deal with the heterogeneous information formats under different criteria, two information transformation mechanisms are developed. Through the proposed information transformation mechanisms, the heterogeneous information formats are unified into interval type-2 fuzzy sets. Then, a new interval type-2 fuzzy distance model is proposed to enhance Besson’s mean ranks in ORESTE method. Based on the proposed distance model, an interval type-2 fuzzy ORESTE method is developed to analyze the conflicts between the alternative sites and select the most desirable one. Finally, an example about the site selection of the WTE system is provided to illustrate the implementation process of our proposal, meanwhile, the comparative analysis and discussions are conducted to verify its superiority and flexibility.

An approach to hesitant fuzzy linguistic multiple criteria group decision making with uncertain criteria weights considering incomparability between alternatives

In multi-criteria group decision-making (MCGDM) problems, the consensus of experts is taken as the result, and it is common that the result may include incomparability between alternatives. The longest ranking of alternatives that attains consensus and allows the incomparability between alternatives is called a maximum consensus sequence (MCS). In decision-making problems related to emerging industry, it is hard to accurately obtain criteria weights. In this case, how to weight different criteria values and individual opinions to mine an MCS is worth studying. This article applies the hesitant fuzzy linguistic ORESTE method to obtain the ranking of alternatives, allowing for uncertain criteria weights and incomparability between alternatives. Then, a compromise-or-not mechanism based on uncertain criteria weights, which can derive experts’ attitudes towards collective result, is developed to tackle the consensus issue. Two kinds of conflicting items about the incomparability in the collective result and divergent opinions of uncompromising experts are identified. Through information exchange among experts regarding the conflicting items, an MCS can be obtained. The proposed method provides an inspiration for MCGDM in emerging industries.

Assessment of regional economic restorability under the stress of COVID-19 using the new interval type-2 fuzzy ORESTE method.

The economic implications from the COVID-19 crisis are not like anything people have ever experienced. As predictions indicated, it is not until the year 2025 may the global economy recover to the ideal situation as it was in 2020. Regions lacked of developing category is among the mostly affected regions, because the category includes weakly and averagely potential power. For supporting the decision of economic system recovery scientifically and accurately under the stress of COVID-19, one feasible solution is to assess the regional economic restorability by taking into account a variety of indicators, such as development foundation, industrial structure, labor forces, financial support and government's ability. This is a typical multi-criteria decision-making (MCDM) problem with quantitative and qualitative criteria/indicator. To solve this problem, in this paper, an investigation is conducted to obtain 14 indicators affecting regional economic restorability, which form an indicator system. The interval type-2 fuzzy set (IT2FS) is an effective tool to express experts' subjective preference values (PVs) in the process of decision-making. First, some formulas are developed to convert quantitative PVs to IT2FSs. Second, an improved interval type-2 fuzzy ORESTE (IT2F-ORESTE) method based on distance and likelihood are developed to assess the regional economic restorability. Third, a case study is given to illustrate the method. Then, robust ranking results are acquired by performing a sensitivity analysis. Finally, some comparative analyses with other methods are conducted to demonstrate that the developed IT2F-ORESTE method can supporting the decision of economic system recovery scientifically and accurately.

T-Spherical fuzzy ORESTE method based on cross-entropy measures and its application in multiple attribute decision-making

T-Spherical fuzzy ORESTE method based on cross-entropy measures and its application in multiple attribute decision-making

Sistem Pendukung Keputusan Perangkingan Dalam Pengajuan Mesin EDC Dengan Metode Oreste

The BCA Merchant analyst team found difficulties in determining the decision to submit the best prospective Merchant because it was still manual. Sometimes it resulted in decisions that were not right on target when they were given but the EDC machine was not used by the business owner because the business location was not strategic and quiet, as a result Bank BCA suffered losses due to spend cost or machine maintenance costs every month. To overcome this problem, decision making for the submission of BCA EDC machines using the ORESTE method is applied so that the problem has been resolved. Ranking in the Oreste Method in this study takes the highest value based on data calculated from predetermined variables and criteria. The end of the calculation based on the Oreste method will give the highest to lowest preference value, the highest result is the best value from the calculation process carried out in the application for the EDC machine and the proper and unworthy merchants are found in its teaching.

Sustainable battery supplier evaluation of new energy vehicles using a distributed linguistic outranking method considering bounded rational behavior

Due to policy promotion towards new energy vehicles, battery supplier evaluation, as a critical multi-faceted decision problem, is the foundation of the good quality of products or service and further long-term development of enterprises. Most of methods have been proposed to measure the performance of potential candidates from the sustainable dimension, but they may ignore resilient and smart criteria, i.e., risk resistance capacity and smart technologies application, relating to normal supply and product reliability. Additionally, prior studies mainly report on the priority of suppliers from perfect rationality of the decision maker, but they pay little attention to indifference and incomparability relations between suppliers and bounded rationality of the decision maker. Therefore, this paper proposes an outranking based multi-criteria behavioral decision making method, named as prospect theory-based distributed linguistic ORESTE method to portray three outranking relations, preference, indifference and incomparability, from the view of bounded rationality of the decision maker. This approach adopts linguistic distribution to reveal the uncertain preference along with good flexibility and adaptability. It is applied to the battery supplier selection in new energy vehicles enterprises. Comparative analysis indicates the availability and superiority and sensitivity analysis verifies its stability.

A Solution Proposal for the Incompleted Preference Structure in the Oreste Method: C-Oreste Iii Method and an Application

A Solution Proposal for the Incompleted Preference Structure in the Oreste Method: C-Oreste Iii Method and an Application

Prioritization of key quality characteristics with the three-dimensional HoQ model-based interval-valued spherical fuzzy-ORESTE method

Ranking key quality characteristics (KQCs) which are widely utilized to evaluate the product quality level and selecting the most important one are necessary for improving the quality of mechanical and electrical product. Many classical ranking methods have been proposed to rank KQCs, e.g., the classical quality function deployment (QFD) method, the classical ORESTE method. However, some drawbacks in constructing ranking framework, rating KQCs/influence factors (IFs) and ranking KQCs are existed in these methods. To solve this problem, we develop a three-dimensional house of quality (HoQ) model-based interval-valued spherical fuzzy-ORESTE (IVSF-ORESTE) method to rank KQCs. First, the three-dimensional HoQ models which add meta-action units (MAUs) dimension are constructed to provide a ranking framework, and interval-valued spherical fuzzy sets (IVSFSs) are utilized to rate KQCs/IFs. Secondly, some new distance and weight distance measures based on the Dice and the Jaccard similarity are proposed to extend the traditional distance measure between IVSFSs. Furthermore, the IVSF-QFD method is used to calculate the importance degrees of IFs and the KQCs are ranked with the IVSF-ORESTE method. Finally, a real case vis-à-vis a NC rotary table is illustrated to explain the implementation process of the proposed method, and discussion results indicate that the proposed ranking method is rational and valid.

A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection

Choosing a good food supply chain is helpful for realizing the coordination of economic benefits and environmental optimization, so as to promote the sustainable development of the society. To solve such a problem, we need to ensure the accuracy of the original information and the validity of the aggregated information. However, experts may not be able to give professional evaluations in some aspects, and a simple ranking of alternatives cannot accurately reflect the relations between alternatives. To solve these problems, this paper proposes a comprehensive method integrating the social participatory allocation network (SPAN) and ORESTE methods under the q-rung orthopair fuzzy environment. To better deal with the imprecise and uncertain information, the q-rung orthopair fuzzy set is adopted in this study to represent decision-makers’ opinions. The delegate mechanism of the SPAN method is introduced to calculate the weights of experts, which make the assessments of alternatives credible. The ORESTE method is used to explore the relations between alternatives in detail. The preference function is used to deal with the case where the data is not ordinal. Finally, a case study concerning the selection of sustainable food supply chains is presented to verify the applicability of the proposed method.

Risk Assessment in Failure Mode and Effect Analysis: Improved ORESTE Method With Hesitant Pythagorean Fuzzy Information

As a system reliability analysis technology, failure mode and effect analysis (FMEA) has been widely used in various industries to reduce the failure risk of products, systems, and services. In recent years, many researchers have found that this technology has limitations in failure mode assessment and failure mode prioritization in complex uncertain environment. In order to solve this problem, this article proposes a new FMEA model, which combines hesitant Pythagorean fuzzy sets (HPFSs) and ORESTE method. Specifically, HPFSs are used to describe the risk assessment information of experts. The ORESTE method is extended to determine the risk priority of the failure modes in FMEA. Moreover, the PIR structure of ORESTE is improved to reduce the subjective influence of experts. Finally, an example of risk assessment of intelligent aquaculture system is given to verify the applicability and effectiveness of the proposed FMEA model. The results show that the proposed FMEA model can not only accurately describe the hesitation and uncertainty of experts’ risk assessment information, but also obtain more suitable risk ranking of failure modes, based on which managers can further take corresponding preventive measures.