Importance Weights Of Criteria Research Articles

Telescopic forklift selection through a novel interval-valued Fermatean fuzzy PIPRECIA–WISP approach

Telescopic forklifts stand apart from other forklift types, boasting numerous benefits. They offer notable advantages, such as enhanced manoeuvrability, accessibility to elevated areas, versatility, and the capacity to operate at high speeds. Choosing appropriate telescopic forklifts can substantially enhance operational efficiency and efficacy within the industry. Concurrently, it can bolster business competitiveness by expediting logistical processes, yielding notable cost reductions. Nonetheless, the intricacy and specificity inherent in these machines complicate the decision-making process for stakeholders. Furthermore, conflicting criteria, the continuous evolution of manufacturers’ models, and the industry’s intricate nature compound the selection challenges. Hence, there is a pressing need for a resilient, dependable, and practical decision-making framework capable of adeptly navigating uncertainties to yield reliable and coherent outcomes. This study aimed to develop an integrated decision-making model based on interval-valued Fermatean fuzzy (IVFF) sets to respond to these requirements and address this critical decision-making problem in the relevant industry, which is also significantly affected by complex uncertainties. This work, therefore, introduces an integrated methodology for decision-making, IVFF–PIPRECIA and IVFF–WISP techniques. IVFF–PIPRECIA determines criteria importance weights, whereas IVFF–WISP identifies optimal alternatives. A case study in the textile industry validates the framework’s practicality. Purchase price emerges as the primary criterion, exceeding 500 thousand euros for telescopic forklifts, followed closely by load-carrying capacity. The second alternative proves to be the best option. Comparative and sensitivity analyses confirm the model’s credibility. The approach effectively handles decision-making uncertainties, yielding competitive outcomes. It can be applied to diverse engineering problems. Insights from this study assist users in selecting optimal equipment and may inform forklift manufacturers in improving machinery. Future research could focus on establishing real-time operational data collection frameworks for these vehicles.

A new comprehensive decision making method under bimodal information

This paper introduces comprehensive and theoretically-driven approach to decision making under bimodal uncertainty in form of Z-numbers. The proposed decision making approach relies on synergy of consistency-driven preferences construction method, eigenvector determination method of Z-number valued matrixes proposed by author and his colleagues and modified WSM model. Consistency-driven preferences construction method is used to obtain a consistent Z-valued pair-wise comparison matrix (PCM) given inconsistent one. Indeed, initial Z-number-valued degrees of pairwise comparison of criteria importance provided by a decision maker are often inconsistent. Next, an eigenvector of the consistent Z-valued PCM is computed to derive criteria importance weights. To arrive at normalized Z-values of criteria, a normalization technique is proposed. Overall evaluations of alternatives are computed as a weighted sum of normalized criteria values. Finally, overall values are compared by using ranking of Z-numbers. The suggested decision method is rank reversal free. Correctness and feasibility of suggested method is illustrated by example.

A comprehensive assessment to offer optimized remediation method for mercury contamination in Musa Bay by using hybrid Fuzzy AHP-VIKOR approach.

Musa Bay, the largest wetland in Iran and one of the most important Hg-polluted media, plays a significant role in the ecosystem of the area and supports many forms of life. Mercury pollution has detrimental effects on the human body and at high levels leads to the loss of microorganisms in marine ecosystems. Hence, a comprehensive assessment for selecting an effective and sustainable remediation method is crucial to restoring the ecosystem promptly. The determination of a proper and practical treatment method not only is a case-based approach, but could be challenging due to its multi-criteria decision-making nature. Considering preferred crucial factors involved in the effectiveness of remedial actions, in this study a questionnaire is designed to assess the opinion of environmental experts, stakeholders, and some occupants of the area on remedial actions based on the importance weights of criteria. Subsequently, practical remediation and management strategies ranked by hybrid FVIKOR as a multi-criteria decision making (MCDM) method. Ranking results show that dredging and stabilization could offer a promising solution for the remediation of the case study. The results of the study demonstrate that the development of MCDM methods along with effective criteria and considering the analysis of the questionnaires, could offer the best remediation strategy for a specific contaminated site.

An extension of TOPSIS method using interval bipolar linguistic neutrosophic set and its application

TOPSIS, known as the “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS), is one of the well-known methods for solving “multi-criteria decision-making” (MCDM) problems. Many TOPSIS methods have been developed to solve real-life problems using neutrosophic sets. However, no study has developed the TOPSIS method under interval bipolar linguistic neutrosophic environments. Therefore, this study aims to present a new concept of “interval bipolar linguistic neutrosophic set” (IBL_NS). IBL_NS is more flexible and adaptable to real-world applications than other sets. Some set-theoretic operations, such as “union”, “intersection”, and “complement”, and the “operational rules” of IBL_NS are defined. Then, a new TOPSIS procedure in IBL_NS is developed. In the proposed IBL_NS-TOPSIS method, ratings of alternatives and importance weights of criteria are expressed in IBL_NS. An application is presented demonstrating the advantages of the proposed IBL_NS-TOPSIS approach.

A Multi-Criteria Decision-Making Model for Selecting the Best Project Delivery Systems for Offsite Construction Projects

Off-site construction (OSC) is an innovative construction method that transfers most of the site-based work to a more controlled environment. Construction waste minimization, speedy schedules, higher sustainability, and better quality are some of the perceived benefits of OSC. Therefore, significant research attention has been given to OSC. However, minimal research attention has been given to procurement management in OSC, which could impact its pace of adoption. Existing studies on the procurement methods of OSC projects have overlooked several criteria related to OSC that impact the selection of the appropriate procurement methods (i.e., design-build, construction management, etc.). In addition, the literature lacks decision-making tools to assist OSC practitioners in selecting the appropriate procurement method. In this regard, this study contributes to the body of knowledge by (1) identifying the criteria that impact the selection of OSC procurement methods; (2) developing a multi-criteria decision-making (MCDM) model to select the appropriate OSC procurement methods. The developed MCDM model uses a hybrid approach of analytic network process (ANP) and evidential reasoning (ER). The ANP, which considers the interdependencies among the collected OSC procurement criteria, is used to calculate the relative importance weights through questionnaire surveys. The ER method evaluates various OSC procurement methods in accordance with the criteria importance weights. The results indicate that project quality, cost control, and funding arrangement are the prominent selection factors. On the other hand, the model reveals that the integrated project delivery (IPD) and construction management (CM) methods have the highest utility scores. The MCDM model has been validated by comparing the results with similar studies. The present study could assist OSC practitioners in selecting the appropriate procurement method for OSC projects.

A Hybrid Multi-Criteria Decision Framework for Selecting Fourth-Party Logistics Service Providers in Fleet Transportation Management: A Case Study in Plastic Resin Manufacturing

Since the selection of the fourth-party logistics service providers (4PLs) has become a crucial strategic decision to innovatively enhance the logistics processes and to reduce logistics costs. Despite a growing interest among practitioners and academicians in shifting the outsourcing of the logistics service to 4PLs, few studies have focused on developing a framework for selection and evaluation. This paper contributes to the literature in proposing a hybrid multi-criteria decision framework to select the best 4PLs in fleet transport management service. The proposed framework is divided into four phases. First, the 4PLs selection criteria are identified through literature review and industrial experts in the field. Second, Decision Evaluation and Experimental Laboratory (DEMATEL) is employed to explore the inter-relationship among selection criteria as well as to analyze the relative importance weights of criteria. Next, a multi-objective optimization model based on ratio analysis (MOORA) is utilized to rank and select the best 4PLs applicant. Finally, the sensitivity analysis is performed to validate the robustness of the proposed framework. One of the major plastic resin manufacturers in Thailand is used as a case study. This study provides the useful insights for selecting and evaluating 4PLs to practitioners and academicians working on this subject.

Evaluation of Covid-19 Pandemic in OECD Countries by Multi-Criteria Decision Making Methods

Amaç: OECD ülkelerinin Covid-19 performanslarına ilişkin kantitatif bir değerlendirme sunma hedefi ile yola çıkılmış, belirlenen parametreler doğrultusunda ülkelerin göreceli bir değerlendirmesini sunmak amaçlanmıştır. 
 Yöntem: Bu amaç doğrultusunda, çok kriterli karar verme (ÇKKV) yöntemlerinden ENTROPI, ARAS ve TOPSIS kullanılmıştır. OECD ülkeleri çalışmanın evrenini oluşturmaktadır. Hollanda, hekim ve hemşire sayılarına ulaşılamadığından, Kosta Rika ise, 25 Mayıs 2021 tarihinde OECD üyesi olduğundan değerlendirme dışı kalmıştır. Çalışma 36 ülke ile gerçekleştirilmiştir. Belirlenen 8 değerlendirme kriteri, Covid-19 pandemisine ilişkin verilerden ve ülkelerin sağlık göstergelerinden oluşmaktadır. Kriterlere ilişkin değerler internet sitelerinden 02.04.2021 tarihinde elde edilmiştir. Verilerin analizinde Excel Programı kullanılmıştır. 
 Bulgular: ENTROPI yöntemiyle kriter önem ağırlıklarının belirlenmesi sonucunda, en az bir doz Covid-19 aşılama oranı (%), 1.000.000 nüfus başına Covid-19 ölüm sayısı, kişi başı cari sağlık harcaması ($), 1.000.000 nüfus başına Covid-19 vaka sayısı ve 1.000 kişiye düşen hastane yatağı sayısı kriterlerinin ilk beş sırada yer aldığı bulunmuştur. ARAS yöntemi sonucunda elde edilen sıralamada ABD, Birleşik Krallık ve İsrail; TOPSIS yöntemi sonucunda elde edilen sıralamada İsrail, Norveç ve Birleşik Krallık üst sıralarda yer almıştır. 
 Sonuç ve Öneriler: Covid-19 pandemi süreci her ne kadar olumsuz olsa da, sağlık sistemleri ve toplumlar için öğretici olmuş, yetersiz kalan alanlarda iyileştirme yapılması ve yeni stratejiler geliştirilmesi gerekliliğini ortaya koymuştur. Covid-19 pandemisi sonrası ülkelerin; sağlık sistemlerinde iyileştirmeler yapmaya, bozulan ekonomilerini yeniden inşa etmeye, gelecekte yaşanabilecek olası salgınlara, krizlere ve evrensel çapta değişikliğe neden olabilecek olaylara hazırlanmaya odaklanmaları önerilebilir.

KOBİ’lerin Reklam Verme Davranışlarının Çok Kriterli Karar Verme Yöntemleri ile Analizi: Sivas Örneği

Businesses promote their products and services to consumers through advertising in order to create a desire to buy. Today, the development of technology offers businesses a wide range of advertising channel options. Choosing the most suitable advertising channel for businesses is a decision problem that requires the consideration of a large number of contradictory criteria. In this study, advertising behavior of SMEs in Sivas was examined with AHP, DEMATEL and maut methods, one of the multi-criteria decision making methods. In the study, the importance weights of the criteria affecting advertising behavior were determined by AHP and DEMATEL methods. Advertising channel selection was made for a company using MAUT method using criterion importance weights determined by AHP and DEMATEL methods. In the study, AHP and DEMATEL methods were found to be applicable methods in the choice of advertising channels along with the Maut method.

Investigation the Effects of Different Social Media Platforms to Companies’ Sales Marketing Processes by Multi-Criteria Decision Making Method

Social media has become a rapidly expanding mass media tool. Today, people spend most of their time on social media and shop here with the developing technology. There are companies that analyze annual social media data and determine the sales and marketing policy by taking these figures into consideration, and arrange their ads accordingly. At this point, this study was conducted with some purposes such as companies should use social media correctly and decide on which social media platform is suitable for their product/service and how to introduce themselves to their customers. In this study, four different social media platforms were evaluated with multi-criteria decision making (MCDM) methods, the social media platform that gave the best result in the ranking was determined and with this way, it was tried to guide the companies that use social media platforms in sales and marketing activities. A multi-criteria model and two-step solution methodology were proposed within the scope of the study for the evaluation of social media platforms. In proposed methodology, the importance weights of criteria were determined by the SWARA method, while the ARAS method was used to evaluate each alternative social media platform. After all calculations, YouTube alternative was found to be more preferable than other alternative social media platforms for digital marketing with the highest utility degree. DOI : https://doi.org/10.54663/2182-9306.2022.v10.n18.133-150

Evaluation of irrigation methods in Söke Plain with HF-AHP-PROMETHEE II hybrid MCDM method

Söke Plain (Turkey) is one of the two plains where cotton production is the highest in Turkey, the leading country for cotton production in the Mediterranean Basin. The cropping pattern in Söke Plain is dominated by cotton with a ratio of 97%. The overall irrigation scheme is equipped with conventional systems (i.e., surface, furrow) whose efficiency is approximately 50% due to high evaporation and physical losses. Water efficiency improvement in cotton irrigation necessitates a thorough evaluation of the agricultural water management for Söke Plain, a water-scarce region under drought threat. In this paper, a hybrid multi-criteria decision making (MCDM) method is presented for the evaluation and selection of irrigation methods. This process involves various potentially conflicting qualitative and quantitative criteria, therefore, a hybrid MCDM method such as HF-AHP-PROMETHEE II is needed to make decisions. In HF-AHP-PROMETHEE II, “Hesitant Fuzzy Analytic Hierarchy Process” (HF-AHP) is first implemented to determine importance weights of criteria and then “Hesitant Fuzzy Preference Ranking Organization Method for Enriching Evaluations II” (HF-PROMETHEE II) is utilized to assess and rank the irrigation method alternatives. For comparison analysis, HF-AHP-TOPSIS (HF-AHP-Technique for Order Preference by Similarity to Ideal Solution) method is also implemented to the same problem. A case study is presented where five irrigation method alternatives in Söke Plain are assessed by five expert decision-makers (DMs), based on fifteen evaluation criteria. Sprinkler is found to be the first ranked irrigation method among five alternatives with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS resulting in the same ranking. The selection of this irrigation technique by the expert DMs is compliant with prevailing regional features related to hydrologic, climatic, environmental conditions and with regard to cotton, one of the highest water-consuming crops.

New additive-consistency-driven methods for deriving two types of normalized utility vectors from additive reciprocal preference relations

In multi-criteria decision making, importance weights of criteria are usually derived from pairwise comparisons and requested for adding up to one. The framework of additive reciprocal preference relations (ARPRs) is a commonly used tool representing pairwise comparisons under the unit interval scale. This paper illustrates that existing additive-consistency-driven utility derivation methods fail to acquire a satisfactory additively normalized importance weight vector of criteria. A normalization framework is introduced under an Abelian linearly ordered group and new methods are proposed to generate additively consistent ARPRs respectively from vectors satisfying new normalization conditions and additively normalized vectors. Two formulas are devised to obtain the two types of normalized utility vectors associated with an additively consistent ARPR. Three optimization models are built and their analytical solutions are found to derive the two types of normalized optimal utility vectors from ARPRs. A geometrically additive consistency index is presented and its approximated thresholds are suggested to check acceptably additive consistency of ARPRs. A stepwise procedure is developed to deal with multi-criteria decision making problems. Two numerical illustrations with comparative analysis and an international exchange postgraduate student selection problem are offered to demonstrate the performance and practicality of the presented models.

A comparative analysis of the circular economy performances for European Union countries

ABSTRACT Circular economy (CE), which has emerged with the integration of environmental science and sustainable development, has a significant contribution to human development and is a constantly developing concept that can be measured at the country, region, city, or enterprise level. Evaluating the CE performances of the European Union (EU) member countries at specific periods is crucial for monitoring their development. This study bridges the gap in the literature in terms of the method, dataset, and comparative analysis used while measuring the CE performances, and this is one of the first studies to look at the importance weights of CE criteria. In this study, a novel approach is proposed to evaluate the CE performances of EU member countries. The evaluation criteria are based on the European Commission CE monitoring framework in the proposed approach. The importance weights of criteria are determined using the fuzzy Simple Multi-Attribute Rating Technique (SMART) approach. The EU member countries are ranked according to their CE performances with the Combinative Distance-Based Assessment (CODAS) method considering the weights of the evaluation criteria. The proposed evaluation approach is applied by taking 2014, 2016, and 2018 years data into account. As a result of the application, according to the CE efficiency, the top five countries are the Netherlands, Luxembourg, Belgium, France, and Germany. The study’s findings can assist researchers and policymakers in gaining a better understanding of countries’ CE performance levels.

Sustainable industrialization performance evaluation of European Union countries: an integrated spherical fuzzy analytic hierarchy process and grey relational analysis approach

ABSTRACT Industrialization, which has changed with the development of innovation and technology, has accelerated the consumption of energy and natural resources while satisfying customer expectations. Sustainable industrialization is an essential concept to meet the needs of present and future generations. There is a critical need to reveal the sustainable industrialization levels of the countries. Countries that can determine their current situation within the scope of sustainable industrialization can also identify open to improvement areas more quickly. In this study, a novel approach is proposed to evaluate the sustainable industrialization performance of European Union (EU) member countries. In the proposed approach, the evaluation criteria consist of 3 main criteria: environmental, economic, and social, with 16 sub-criteria. The importance weights of criteria are determined by the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) then countries are ranked according to sustainable industrialization performance with the Grey Relational Analysis (GRA) method considering the weights of the evaluation criteria. The proposed method is applied to EU member countries, taking into account the 2018 data. As a result of the application, according to the sustainable industrialization performance, the top five countries are determined as Sweden, Germany, Netherlands, Luxembourg, and Denmark. This study is among the first to evaluate sustainable industrialization performances of EU member countries. The study’s outcomes can help researchers and policymakers have an opinion about the sustainable industrialization levels of countries

An integrated approach in selecting the optimal insulation plaster mortar series

In this study, an integrated approach by Taguchi, Analytic Hierarchy Process [AHP] and Simple Additive Weighting [SAW] method was proposed to find out the optimal insulation plaster mortar series, based on multiple criteria. Firstly, Taguchi method was applied to define the experimental design plan, with the factors of cement, lime, dolomite and perlite in three levels for each with L9 orthogonal design. Then, ultrasonic pulse velocity, compressive strength, bond strength, capillarity water absorption and thermal conductivity experiments, were made according to the design. The importance weights of criteria were obtained by AHP and the scores of the series were calculated by SAW method. The factors’ optimum levels were obtained based on the scores and the optimal series was proposed.

Application of F-WASPAS in the Ranking of Crops for Agro-Processing: The Case of Ikondo Ward in Njombe, Tanzania

The purpose of this work was to develop and apply a Fuzzy Weighted Aggregated Sum Product Assessment (F-WASPAS) method in ranking selected crops for agro-processing at Ikondo Ward in Njombe Region, Tanzania. The fuzzy technique for order preferences by similarity to ideal solution (TOPSIS) was applied in determining the fuzzy importance weights of criteria, while the fuzzy WASPAS successfully ranked the crops, and maize was ranked the highest.
 Keywords: F-WASPAS, Linguistic variables, Fuzzy aggregation, Agro-processing, Decision making, Multi-Criteria Decision Making.

A group multicriteria decision making with ANOVA to select optimum parameters of drilling flax fibre composites: A case study

Composite parts are often drilled during assembly. However, it has been well established that drilling process can damage long-fibre composites, and the ideal process parameters need to be investigated based on each given material system, yet under different conflicting design criteria. Here, a multi-criteria decision making (MCDM) approach along with the analysis of variance is aimed to find the best-compromised solution for drilling parameters of a flax fibre composite plate; namely to minimize the top and bottom surface delamination factors while simultaneously maximizing the residual tensile strength of the drilled laminate. Different criteria importance weights along with different MCDM techniques have been modeled to capture different practical design scenarios. Overall, the majority of employed methods suggested a higher spindle speed, a lower feed rate, and a step drill bit geometry. Among the design factors, the feed rate by far played a statistically significant role (>95% confidence level) in controlling the damage outcome and is deemed of prime design concern. It is also shown that the inclusion of subjective weights by experts is a key in such design problems to avoid statistical overinterpretation.

AHP-TOPSIS social sustainability approach for selecting supplier in construction supply chain

Prequalification of suppliers in the Construction Supply Chain is considered a crucial step to assure to their ability to deliver socially sustainable projects. This research identifies the most important social sustainability prequalification criteria for supplier selection in Construction Supply Chain. Additionally, a Multi-Criteria Decision Making (MCDM) model based on social indicators of sustainability is proposed in this research. Structured interviews were organized with experienced practitioners to define the relative importance weights of criteria that have collected in the first phase using Analytic Hierarchy Process (AHP). As such, the AHP is applied to develop mathematical determination to achieve the weights of social indicators. Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method is used to evaluate the different suppliers in the construction supply chain against 17 identified attributes. Ultimately, the closeness coefficients of the suppliers are estimated in order to identify social performance. The research aims at proposing a computational model of MCDM in order to introduce it to the construction organizations to utilize in the supplier prequalification process. A computational model is developed and a case study is worked out to illustrate the proposed methodology in supplier selection to ensure sustainable construction projects. Afterwards, the model is validated and a sensitivity analysis is conducted to analyze the impact of changing the weights of the considered attributes in the model outputs.

SUPPLIER SELECTION PROCESS IN DAIRY INDUSTRY USING FUZZY-TOPSIS METHOD

Supplier selection is one of the most critical processes within the purchasing function. Choosing the right supplier makes a strategic difference to an organization’s ability to reduce costs and improve the quality of products by helping to select the most suitable supplier. Sütaş Dairy Company, which is entered to Macedonia market in 2012. In the dairy company, there is only one purchasing manager who selects the farmers. Importance weights of criteria are determined using his reference, and also the alternatives are evaluated according to each criterion. The most important criteria are product and other costs, the price is also playing an important role, but due to the small marketplace of Macedonia, the prices are almost the same in every region. To select the dairy supplier in Macedonia, Fuzzy-TOPSIS technique is used. The main goal of using fuzzy logic in this study is to help decision-makers for identifying the importance of selection criteria and rank possible suppliers easily. Since the supplier selection process is a Multi-Criteria Decision Making (MCDM) problem, after identify the weights and rankings in a fuzzy environment, TOPSIS algorithm has been used in the rest of the problem. Finally, fuzzy TOPSIS methodology has been implemented successfully, and its result pointed out the most suitable suppliers.

The Interactive Weighting Method Concerning Consistency, Inadequacy, Complementary and Supplementary Properties of Criteria

In most multicriteria decision-making methods, several options are ranked according to numerous criteria. In the decision-making process, experts often determine the importance weight of the criteria by comparing them to each other or with ideal solutions. With increasing criteria, the decision-making process becomes more complex, and the compatibility of judgments is reduced. Another problem is the inadequacy of criteria at different levels of the decision-making process. A high-level criterion can be considered, which includes several subcriteria. The subcriteria considered may not include all of the possible subcriteria because they could be unknown to decision-makers or could not be measured and used by decision-makers. Hence, the assumption that the importance weight of the subcriteria equals one (for example, in the analytic hierarchy process method) may not always be accurate. In this article, a new decision-making method is proposed based on Shapley's value that can extract the importance weight of criteria at different levels by considering the consistency between subcriteria. Additionally, an interactive top–down decision-making approach is presented for compatible judgments. The proposed method is applied to determine the importance weights of criteria in a sustainable supplier selection problem, and we show how the method could facilitate the extraction of the importance weight and address the inadequacy and dependency properties between the criteria.

Factor relation analysis for sustainable recycling partner evaluation using probabilistic linguistic DEMATEL

Evaluating and selecting suitable sustainable recycling partners is a key work in sustainable supply chain management. In order to deal with the probabilistic linguistic influence relations between criteria and obtain the key factors that influence the evaluation results of sustainable recycling partners, we propose a new decision-making trial and evaluation laboratory (DEMATEL) method. First, we propose a new generalized weighted ordered weighted averaging (GWOWA) operator and discuss its properties. Second, we use probabilistic linguistic term sets (PLTSs) to aggregate the experts’ hesitant fuzzy linguistic decision-making information and develop a novel method of transforming PLTSs into triangular fuzzy numbers (TFNs) based on the proposed GWOWA operator and the characteristics of PLTSs. Furthermore, we propose a method of making criteria relation analysis based on DEMATEL with TFNs. With the method, we not only access the importance weights of criteria but also obtain the influence relation among the criteria and cluster the criteria into two groups: cause group and effect group. Finally, we apply our method to a real case of sustainable recycling partner selection.