Ranking Of Alternatives Research Articles

Financial and Environmental Performance Analysis of Logistics company on the Fortune 500 By MEREC-based AROMAN Methods

This study aims to examine the financial and environmental performance of a logistics company listed in the Fortune 500 Türkiye over the years. The current study is carried out within the scope of Ekol Logistics, one of Türkiye’s leading logistics companies. The data is obtained from the Fortune 500 Türkiye and Ekol’s Sustainability reports. In this study, a hybrid model integrating the method based on the removal effects of criteria (MEREC) and alternative ranking order method accounting for two-step normalization (AROMAN) method is employed. The MEREC findings showed that net sales change was the most significant criterion, while equity was the least significant criterion in the assessment of financial performance. Moreover, number of vehicles equipped with EURO 6 technology was the most significant criterion, while water consumption was the least significant criterion in the assessment of environmental performance. The AROMAN findings pointed out that Ekol's achieved the most outstanding financial results in the years 2020, 2021, and 2022. Additionally, Ekol achieved notable environmental performance in 2022. Moreover, sensitivity and comparative analysis are conducted to observe the validity of the results.

Optimalisasi Pemilihan Supplier Komponen Fabric pada Produk Man Shirt X Menggunakan Metode Analytical Hierarchy Process

PT. ABC is a company engaged in the production of ready-to-wear clothing. The main raw materials use fabric from various suppliers. The problem is the poor quality of the fabric raw materials and late delivery from suppliers, which has an impact on production optimization. Supplier selection is a strategic activity, especially if the supplier will supply critical items and be used in the long term. Good raw materials will produce good products. Choosing the right supplier can provide benefits for the company so that the production process runs smoothly. This study aims to determine the best supplier according to the specified criteria using the Analytical Hierarchy Process (AHP) supplier selection method in the selection of fabric component suppliers at PT. ABC. Supplier selection uses the AHP method with subjective assessment input from the company. The expectation of the final result can determine the ranking of alternatives so that it produces the best supplier based on criteria that are in accordance with the company. Based on the results of processing using the AHP method, the order of criteria obtained is quality (0.6554), delivery (0.1867), and price (0.1577). The alternative selection of raw material suppliers with the highest priority is supplier X with the best score of 1.358. This shows the most optimal supplier value in fulfilling the needs of fabric raw materials according to the criteria required by the company.

Optimalisasi Pemilihan Supplier Komponen Fabric pada Produk Man Shirt X Menggunakan Metode Analytical Hierarchy Process

ABC is a company engaged in the production of ready-to-wear clothing. The main raw materials use fabric from various suppliers. The problem is the poor quality of the fabric raw materials and late delivery from suppliers, which has an impact on production optimization. Supplier selection is a strategic activity, especially if the supplier will supply critical items and be used in the long term. Good raw materials will produce good products. Choosing the right supplier can provide benefits for the company so that the production process runs smoothly. This study aims to determine the best supplier according to the specified criteria using the Analytical Hierarchy Process (AHP) supplier selection method in the selection of fabric component suppliers at PT. ABC. Supplier selection uses the AHP method with subjective assessment input from the company. The expectation of the final result can determine the ranking of alternatives so that it produces the best supplier based on criteria that are in accordance with the company. Based on the results of processing using the AHP method, the order of criteria obtained is quality (0.6554), delivery (0.1867), and price (0.1577). The alternative selection of raw material suppliers with the highest priority is supplier X with the best score of 1.358. This shows the most optimal supplier value in fulfilling the needs of fabric raw materials according to the criteria required by the company.

A Multi-Criteria Method Integrating Distances to Ideal and Anti-Ideal Points

Multi-criteria decision-making methods based on reference points and distances from them are essential for evaluating alternatives across multiple criteria. These methods provide structured approaches to comparing and ranking alternatives relative to specified reference points. The main objective of this paper is to present the Multi-Criteria Method Integrating Distances to Ideal and Anti-ideal Points (MIDIA), which, through a weighted system, allows for the consideration of balance and asymmetry in assessing alternatives based on their distances from the ideal and anti-ideal points. As a multi-criteria algorithm, MIDIA is user-friendly and reflects the human mind’s natural tendency to assess objects based on fundamental concepts—comparison with the ideal solution and the anti-ideal solution—that are familiar from everyday experiences and provide valuable insights from a behavioral perspective. Moreover, the proposed method can be seen as an extension of Hellwig’s approach, designed to facilitate the ranking of alternatives based on two reference points: the ideal point and the anti-ideal point, measuring the distance between the alternative and the ideal point and the distance between the ideal and anti-ideal points. The MIDIA method integrates elements from both TOPSIS and VIKOR, by incorporating the structure of TOPSIS and the compromise perspective of VIKOR, offering a balanced approach to multi-criteria decision-making by focusing on the distances from ideal and anti-ideal points. Illustrative examples are given to demonstrate the usability of the proposed tool in situations where the decision-maker has asymmetrical preferences concerning the importance of ideal and anti-ideal points in ranking alternatives. Moreover, the MIDIA method is applied to one of the Sustainable Development Goals, in the area of education (SDG4), to obtain the rankings of EU member countries in 2022. The results obtained using the MIDIA method were compared with those obtained using the TOPSIS and VIKOR approaches. The study concludes that the ranking of alternatives depends on the coefficients of the importance of the distances to reference points and the data setup.

PENERAPAN MODEL WATERFALL DALAM MERANCANG APLIKASI PEMILIHAN SISWA TELADAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING

By having exemplary students, it is hoped that students at school will have good role models in all aspects. Unfortunately, subjective selection because it is done using voting can lead to unhealthy competition. So far, the selection of exemplary students begins with the selection of students with the highest average scores, then looks at the student's activity and record of violations which culminates in a vote carried out in the exemplary student selection meeting. Voting at the end of the election can cause the selection of exemplary students to no longer be objective and no longer fair. The application design will use the waterfall method by implementing the SAW method as a method used to help make decisions. The criteria used are 7 criteria in accordance with school policy and the results of this analysis, first the system is able to record all students who will be alternative exemplary students and also the criteria set in accordance with school policy. Second, by implementing a decision support system using CBIS, it can minimize the objectivity and complexity of stakeholders in making decisions and can increase data accuracy. Third, based on the management using this decision support application, an alternative ranking of exemplary students was obtained with the first alternative position being Siska Azzahra Shafa with a total score of 19,790, the second alternative being Andrawan Erlang Padana with a total score of 19,654 and the third being Ichsan Sandi with a total score of 19,645.

Multi-Criteria Decision-Making Approach for Pre-Synthesis Selection of the Optimal Physicochemical Properties of TiO2 Photocatalytic Nanoparticles for Biomedical and Environmental Applications.

Nanomaterials are widely used in several biomedical and environmental applications, due to their ideal properties. However, the synthetic and characterization procedure requires significant costs and has a negative environmental impact. Various methods are available in order to control the pre-synthesis design of the produced materials, predicting their behavior and minimizing the series of experiments. Multi-Criteria Decision-Making is proposed in this study in order to determine the best combination of the physicochemical parameters and to define the best alternative among fifteen different samples of nanostructured titanium dioxide. In particular, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was applied to achieve a final ranking of the available alternatives by avoiding several of the trials that would follow testing the biological effect and the photocatalytic degradation of organic pollutants. Thus, this approach helps us to stay environmentally and ethically correct, saving time, money, and energy and also providing an optimization of the nanomaterials that are developed.

Use of the TOPSIS method for hydro-chemical classification of some bottled waters marketed in Algeria

The bottled water market in Algeria has experienced significant expansion in recent years, driven by increased demand and the growing number of production units. Although the quality of these waters generally meets health standards, notable variations remain in terms of mineral composition and organoleptic characteristics. To refine the assessment of this quality, this study proposes an innovative methodological approach based on the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique. This method allows ranking alternatives based on their proximity to an ideal solution, taking into account criteria such as hardness, nitrate content, mineralization, and the hydro-chemical nature of the waters. The quality of the studied waters varies according to the analyzed parameters, and the importance of the criteria is determined by their impact on the potability and taste of the waters. Hardness is considered essential, followed by mineralization and hydro-chemical nature, while nitrate content is the most crucial criterion due to potential health risks. A detailed ranking of the different brands available on the Algerian market has been established. The results reveal a great diversity of profiles, with no brand systematically standing out from the others.

Assessing the Impact of Criterion Weights on the Ranking of the Top Ten Universities in Vietnam

This study focuses on evaluating the influence of criterion weights on the ranking of the top ten universities in Vietnam. Criteria weights were determined using four different methods, including the equal weight method, the weights of the Vietnam University Rankings (VNUR) system, the entropy weight method, and the Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) weight method. Four university ranking methods were applied: Proximity Indexed Value (PIV), Ranking of Alternatives with Weights of Criterion (RAWEC), Root Assessment Method (RAM), and Simple Ranking Process (SRP). The results indicate that the use of different weight calculation methods does not significantly affect university rankings. The four leading universities in Vietnam consistently maintain their position in the rankings, regardless of the weight calculation or ranking methods used.

PSI-SAW and PSI-MARCOS Hybrid MCDM Methods

This paper presents a study on the hybridization of Multi-Criteria Decision-Making (MCDM) methods: Preference Selection Index (PSI), Simple Additive Weighting (SAW), and Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS). The hybridization was conducted between the PSI and the other two methods, resulting in new methods, namely PSI-SAW and PSI-MARCOS. For each specific problem, applying these two hybrid methods to rank alternatives among the available options produces three different sets of rankings: one created by PSI, one by the hybrid PSI-SAW, and one by the hybrid PSI-MARCOS. The accuracy of the proposed models was tested in three different cases. The test results show that both proposed models exhibit high accuracy. This study provides users with highly accurate and useful methods for MCDM.

Analyzing energy transition for industry 4.0-driven hybrid energy system selection with advanced neural network-used multi-criteria decision-making technique

This study aims to select the appropriate renewable energy alternatives for the efficiency of hybrid energy systems to increase energy transition performance. For this purpose, a novel neural network (NN)-based fuzzy decision-making model is constructed that has three different stages. In the first stage, NN-based fuzzy decision matrix is created. Secondly, 6 different variables based on industry 4.0 are weighted with the sine trigonometric Pythagorean fuzzy entropy technique. Additionally, another calculation has been implemented with criteria importance through intercriteria correlation (CRITIC) to identify the consistency of the results. Furthermore, in the third stage, considering 5 different renewable energy alternatives, 10 different combinations are identified for hybrid energy systems. The most effective alternatives are defined by the sine trigonometric Pythagorean fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS) method. Moreover, to test the validity of these results, another analysis is conducted using the additive ratio assessment (ARAS) technique. The main contribution of the study is that the optimal renewable energy combination required for an efficient hybrid energy system is determined by performing a priority analysis between the variables. This situation has a significant guiding feature for investors. Similarly, the development of the RATGOS technique both increases the methodological originality of the study and enables more accurate alternative ranking. It is identified that the results of all methods are similar. Therefore, this situation gives information about the coherency and validity of the findings. It is concluded that the most important criterion is real-time capability. It is also denoted that the best combination for hybrid energy systems is Solar-Wind.

Penerapan Metode Simple Additive Weighting (SAW) Dalam Sistem Pendukung Keputusan Pemilihan Kapal Sebagai Moda Transportasi Laut

Maritime transportation has become the primary choice for Indonesian society due to its ability to carry passengers and goods in large quantities at relatively low costs. Based on data from the Indonesian Ministry of Transportation, there are 306 ships operating in domestic crossings, with 118 managed by ASDP Ferry Indonesia, 170 private ships, and 18 BUMF ships. Based on deep learning, this study aims to assist students of the Selaparang Lombok Yogyakarta dormitory in recommending the best ship selection for the Surabaya-Lombok route and vice versa. The decision support system is evaluated based on criteria including ticket prices, travel time, travel comfort, facilities, ship capacity, safety, departure schedule regularity, and operator reputation. This study uses a simple Weighted Evaluation Method called Simple Additive Weighting to determine the best alternative ranking. The results show that the comparison test between the system calculation and Microsoft Excel calculation results in 100% similarity. KMP Kirana VII occupies the first rank with a value of 0.95, making it the best ship solution suitable for student use

The Deck-of-cards-based Ordinal Regression method and its application for the development of an ecovillage

This paper presents the deck-of-cards-based Ordinal Regression (DOR), a new multicriteria decision-aiding procedure that conjugates the deck-of-cards method with an ordinal regression approach to define a multicriteria value function representing the preferences of the decision maker (DM). The deck-of-cards method allows the DM to express the ranking order of a set of reference alternatives along with the intensity of preferences between reference alternatives. An ordinal regression procedure is then used to define a multicriteria value function that represents the ranking of the reference alternatives as well as the preference intensity. This approach can be applied to define value functions with different formulations, such as weighted sum, additive value, or Choquet integral. The value function thus obtained can be used to comprehensively evaluate alternatives of a multi-criteria decision problem. The value function provided by DOR can also be applied to a multi-objective optimisation problem. In this study, we applied DOR to handle urban and regional planning decisions in which facilities are required to be selected, located, and planned. In particular, we consider the interactions between criteria and synergies between facilities in an enriched version of the so-called space–time model. We applied this methodology to a real-world problem to plan the development of a sustainable ecovillage in the province of Turin (Italy), thus supporting the president of the cooperative owning the ecovillage in his decisions regarding which structures to select, where to locate them, and when to plan their realisation.

Comparison of the Results of the Edas and Vikor Methods in the Decision Support System for KIP Scholarship Recipients at Malikussaleh University

Many high school graduates do not go on to higher education due to the high cost of education. To address this issue, the government, educational institutions and related parties can work together to find solutions to reduce financial barriers and increase access to higher education. In finding prospective students who are eligible to receive scholarships, the government must be fair and precise in making decisions regarding KIP scholarship recipients. This research uses EDAS and VIKOR methods in the selection of prospective KIP scholarship recipients at Malikussaleh University. This study uses historical data of previous KIP scholarship recipients as test data, where there are 6 criteria used, namely parent status, parent income, number of parent dependents, parent employment, parent home ownership, and parent home area. The application of the EDAS method resulted in Fauzi (230510004) as the first rank with an AS value of 0.850; then Hernita Ceria (230180023) as the second rank with an AS value of 0.791; and Ipadayan (230340033) as the third rank with an AS value of 0.789. In the application of the VIKOR method results, Halimah Murni (230210176) as the first rank with a Q value of 0.000; then Nauval Alzabar (230110077) as the second rank with a Q value of 0.015; and Muhammad Bukhari (230110040) as the third rank with a Q value of 0.024. 4. The results of this study state that the EDAS and VIKOR methods are methods that have different types. The EDAS method ranks alternatives based on their distance from the average solution, resulting in a ranking of alternatives based on how close they are to the optimal solution. While the VIKOR method ranks alternatives and provides the best compromise solution that best matches the applied criteria.

Prioritization of sustainable development plannings for supply chain finance using a novel Triangular neutrosophic-based TOPSIS-CPT-VIKOR model

The development of sustainable supply chain finance (SSCF) promotes the improvement of the long-term production and operational performance of enterprises. It is significant to explore both environmentally friendly and cost-effective solutions, especially in the presence of uncertain information. The triangular neutrosophic number (TrNN) can enable decision-makers (DMs) to express their preferences in high uncertainty. This paper aims to provide a systematic multiple-attribute group decision-making (MAGDM) framework to support DMs in prioritizing sustainable development plannings by combining the best-worst method (BWM), optimization model of maximizing deviation method, and uniformity entropy theory. Moreover, a TrNN-based extended TOPSIS method is developed to measure the differences in DMs’ importance. We incorporate the cumulative prospect theory (CPT) method to account for DMs’ psychological behaviors in risk scenarios. The CPT-VIKOR methodology is employed to rank alternatives, enhancing the precision of decision-making. Finally, the proposed approach is successfully applied to the LNG industry to illustrate its applicability.

Ranking willingness to reuse water in cotton irrigation with hybrid MCDM methods: Soke plain case study

Soke Plain, located within the Büyük Menderes River Basin is one of the highest producers of cotton in Türkiye. The overall irrigation water supply is based on scarce conventional water resources that are being depleted at an increasing pace due to climate change impacts in B. Menderes. The inclusive objective of this research is to pave the way for a "water efficiency action plan" incorporating non-conventional (alternative) water resources for irrigation in Soke Plain to address adaptive management. Integrated Water Resources Management (IWRM) principles help decision makers (DMs) to identify and apply the most adequate alternatives among other possible ones in resource planning processes. Therefore, the preference ranking of DMs among possible water resource alternatives for irrigation is vital for implementation. This paper marks the first instance of using a multi-criteria decision-making (MCDM) method to evaluate both conventional and non-conventional water resource alternatives for cotton irrigation. The evaluation and ranking of water resource alternatives is processed using the hybrid MCDM method, integration of “Hesitant Fuzzy-Analytic Hierarchy Process” (HF-AHP) and “Hesitant Fuzzy Evaluation based on Distance from Average Solution” (HF-EDAS), namely HF-AHP-EDAS. This procedure implies several possibly contradictory qualitative and quantitative criteria, incorporates ambiguity, vagueness, and hesitancy in decision-makers’ decisions, and achieves a consistent, dependable ranking of alternatives. Eight different water resources for irrigation are evaluated by 5 experts, for 15 assessment criteria, in Soke Plain. Conventional water resources blended with drainage water is concluded to be the best irrigation water resource alternative, with HF-AHP-EDAS and also with HF-AHP-PROMETHEE II (Preference Ranking Organization Method for Enriching Evaluations II), that is used for comparison analysis. This choice aligns well with the outlined arguments, culminating in an overall result deemed compliant with the field survey.

MEREC-MABAC method based on cumulative prospect theory for picture fuzzy sets: Applications to wearable health technology devices

Since there is a causal connection between the performance of the alternative with criteria removed and the assessment of the criteria weights, Method based on the Removal Effects of Criteria (MEREC) can reflect the objectivity of statistical data from this new perspective. Multi-Attributive Border Approximation area Comparison (MABAC) approach considers the subjective psychological characteristics of decision makers (DMs), particularly personal preferences and cognitive limitations, through expert scoring. Cumulative prospect theory (CPT) takes into account both potential gains and losses. We propose applying the MEREC method to picture fuzzy sets (PFS) for the first time to determine criteria weights. We suggest an alternate ranking approach for the CPT-MABAC algorithm based on the Hamming distance of the picture rejection membership degree that corresponds to four behavioral states: acceptance, opposition, abstention, and rejection. We develop the PFS-MEREC-CPT-MABAC evaluation framework to tackle the multiple attribute decision-making (MADM) problems while evaluating the performance of wearable health technology devices (WHTDs). The model achieves a compromise between objectivity and subjectivity as well as capturing the psychological behavior of the experts. Finally, in order to determine the soundness and effectiveness of this integrated research approach, sensitivity and comparison analysis are done to compare the results of its operation with those of existing models.

Mining Enterprise Production Line Optimal Load Modelling

The article is devoted to the issues of the mining enterprise production line optimal load model. A large number of issues to related to alternative production plan implementation transition are considered in various works. A mathematical model to form an optimal plan mining enterprise raw material mixture from deposits is proposed in the study. A method of multi-criteria alternative ranking in terms of integral efficiency indicator with the following problem solution of optimal plan determination for a raw material mixture from deposits was chosen for that purpose. The article proposes an approach to determine the production line optimal loading plan of a mining enterprise based on the creation of an ore mixture with the highest utility. The value of a particular deposit is determined by a variety of factors, including the distance from the production line, the ore content in the rock, and the volume of the deposit. The paper shows that the development of a specified field management can be implemented based on solving linear programming problems. The hierarchy contains three levels: the system purpose; the factors influencing the deposit appeal (the metal content, the deposit volume, and transport accessibility); alternatives (deposits of raw materials directly). Let's assume that it is necessary to find the maximum efficiency by means of an ore mixture from the given deposits. Resource restrictions are imposed on the task: the work and machine time fund, the amount of first type reagent, and the amount of second type reagent. The composition of the constraint vector can be set depending on the value of the resources. The study found that the optimal plan is implemented under the complete resource utilization both of the first and the second types and a fifty-three percent level of the third resource utilization. Despite the low integral assessment of the raw material value of the fourth deposit, which is mainly determined by the low ore content in the rock, with respect to other deposits, its maximum utilization is also recommended, which in turn, is determined by the low resource intensity of ore extraction from this rock.

Optimized Grid Partitioning and Scheduling in Multi-Energy Systems Using a Hybrid Decision-Making Approach

This paper presents a thorough review of our state-of-the-art technique for enhancing dynamic grid partitioning and scheduling in multi-energy source systems. We use a hybrid approach to T-spherical fuzzy sets, combining the alternative ranking order method accounting for the two-step normalization (AROMAN) method for alternating ranking order to enable two-step normalisation with the method based on removal effects of criteria (MEREC) for eliminating criteria effects. This enables us to obtain the highest level of accuracy from our findings. To ascertain the relative importance of these criteria, we use MEREC to perform a rigorous examination of the influence that each evaluation criterion has on the outcomes of the decision-making process. In addition, we use AROMAN to provide a strong foundation for assessing potential solutions by accounting for spherical fuzzy sets to account for any ambiguity. We illustrate how our approach successfully considers several factors, such as social acceptability, technical feasibility, environmental sustainability, and economic feasibility, through the analysis of an extensive case study. Our approach provides decision-makers (DMs) with a rigorous and rational framework for assessing and choosing the best grid division and scheduling options. This is done in an effort to support the administration and design of resilient and sustainable multi-energy systems. This research contributes to the growing body of knowledge in this area by offering insights that help to direct policy, planning, and investment decisions in the shift towards more sustainable energy infrastructures. Moreover, it adds to the growing body of information on multi-criteria decision-making (MCDM) in energy system optimization.

Branching-independent random utility model

This paper introduces a subclass of the Random Utility Model (RUM), called branching-independent RUM. In this subclass, the probability distribution over the ordinal rankings of alternatives satisfies the following property: for any k∈{1,…,n−1}, where n denotes the number of alternatives, when fixing the first k and the last n−k alternatives, the relative rankings of the first k and the last n−k alternatives are independent. Branching-independence is motivated by the classical example due to Fishburn (1998), which illustrates the non-uniqueness problem in random utility models. Surprisingly, branching-independent RUM is characterized by the Block-Marschak condition, which also characterizes general RUM. In fact, I show that a construction similar to the one used in Falmagne (1978) generates a branching-independent RUM. In addition, within the class of branching-independent RUMs, the probability distribution over preferences is uniquely determined. Hence, while branching-independent RUM has the same explanatory power as general RUM, it is uniquely identified.

A regret theory-based even swaps method with complex linguistic information and its application in early-stage lung cancer treatment selection

Lung cancer is the cancer with the highest morbidity and mortality rate, and selecting treatment options for early-stage lung cancer patients is of great significance in improving cure rate. To help individuals make rational decisions, the even swap method, a multiple criteria decision-making (MCDM) model, provides an effective mechanism to make tradeoffs between criteria; however, the original even swap method ignored psychological characteristics of individuals and could not deal with complex linguistic information. To deal with the early-stage lung cancer treatment selection problem, this paper introduces generalized probabilistic linguistic term sets (GPLTSs) to describe complex linguistic information and proposes a generalized probabilistic linguistic even swap method based on the regret theory. Firstly, the upper and lower bounds corresponding to linguistic expressions are extracted to represent the uncertainty of GPLTSs. Then, a regret-rejoice function is introduced to express psychological characteristics of individuals when they making tradeoffs between criteria. Afterwards, a regret theory-based even swap method is proposed to rank alternatives. The proposed method is validated in the selection of early-stage lung cancer treatment options. Sensitivity analysis and comparative analysis are given to show the feasibility of the proposed method.