Multi-criteria Decision-making Method Research Articles

Multi-Criteria Decision Making (MCDM) Approach for Identifying Optimal Solar Farm Locations: A Multi-Technique Comparative Analysis

This study explores the spatial suitability for solar farm placement using Geographic Information System (GIS) techniques (ArcGIS Pro 3.0.2) coupled with Muti-Criteria Decision-Making (MCDM) methods. Nine evaluation criteria significantly impacting solar farm placement in Erbil, Iraq were selected, and the Analytic Hierarchy Process (AHP) was utilized to assign proper weights to these criteria. Suitability maps were derived and classified using three MCDM methods: Weighted Overlay (WO), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and SAW (Simple Additive Weighting) to establish comparisons. Discrepancies were noticeable between the outcomes of these methods, with distinctions observable across most categories. The validation process illustrated superior performance by SAW model, closely followed by TOPSIS model, while the weighted overlay model showed significant differences. The southeastern region of Erbil governorate was identified as the most suitable area for solar farm construction due to favorable criteria values and potential for future expansion. This approach massively facilitates locating and evaluating ideal areas for solar farm construction, thereby minimizing the time, financial resources, and efforts dedicated towards this endeavor.

Management excellence practices in small- and medium-sized industries: proposition of an evaluation approach and application in an emerging country

PurposeThis paper proposes an evaluation approach for analyzing excellence management practices at a regional level based on experts’ assessment.Design/methodology/approachUsing the National Quality Foundation’s Management Excellence Model (MEG), 19 management excellence practices were identified and tailored for small- and medium-sized industries (SMIs). Data were collected through a survey with 25 experts who assessed these practices in the context of Brazilian manufacturing SMIs. The analysis utilized Fuzzy TOPSIS Class (FTC), and a sensitivity analysis was also conducted.FindingsThe proposed evaluation approach integrates a reference model for management excellence (MEG), an analysis method incorporating uncertainty (FTC), and results that enable decision-makers to make well-informed choices. Of the 19 practices assessed, 15 were classified as “unacceptable,” while four were rated as “regular,” and none as “expected.” Key challenges relate to practices in information security, knowledge, innovation and change management.Research limitations/implicationsThe study’s primary limitation is the use of non-probabilistic sampling and its focus on the Brazilian context. However, the extensive knowledge and experience of the experts in manufacturing SMIs and the need for studies addressing specific regional contexts should be noted.Practical implicationsThe findings reveal a significant gap between ideal management practices and the actual state of SMIs, especially in emerging markets.Originality/valueThis research introduces a novel approach that combines a reference model tailored for SMIs with a multicriteria decision-making method, offering valuable insights for decision-makers and guiding future research.

Optimal Routing of Gas Pipelines in Seismic Regions Using an Efficient Decision-Support Tool: A Case Study in Northern Greece

High-pressure gas pipelines are significantly vulnerable to earthquake-related geohazards (tectonic faulting, slope instabilities, and/or soil liquefaction phenomena). Avoiding geohazardous areas is not always techno-economically feasible, as it would increase the length and cost of the infrastructure. Conversely, crossing these areas may adversely affect the structural performance of the pipeline, leading to unfeasible mitigation measures. Thus, selecting cost-effective, safe, and resilient routing is crucial. This study presents a GIS-based decision-support tool for optimal routing, taking into account, among other criteria, earthquake-related geohazards. The proposed tool considers not only the aforementioned but also more complex earthquake-related geohazards, such as secondary fault ruptures that are non-parallel or even perpendicular to the main fault, which might have been overlooked during the design of existing pipelines. To validate its effectiveness, the present tool is applied in a real case study in northern Greece, where the aforementioned earthquake-related geohazards coexist. Through a GIS-based multi-criteria decision method, various scenarios are examined by assigning different weights to the adopted criteria, and several cost-minimized routes are derived. This tool could be highly beneficial for the pipeline industry since it can assist operators and stakeholders in selecting the optimal pipeline route in geohazardous areas.

An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making

The design of an Active Reflective Surface Control System (ARCS) is a complex engineering task involving multidimensional and multi-criteria constraints. This paper proposes a novel methodological approach for ARCS design and optimization by integrating Axiomatic Design (AD) and Multi-Criteria Decision Making (MCDM) techniques. Initially, a structured design plan is formulated within the axiomatic design framework. Subsequently, four MCDM methods—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Entropy Weight Method (EWM), Multi-Criteria Optimization and Compromise Solution (VIKOR), and the integrated TOPSIS–Grey Relational Analysis (GRA) approach—are used to evaluate and compare the alternative solutions. Additionally, fuzzy information axioms are used to calculate the total information content for each alternative to identify the optimal design. A case study is conducted, selecting the optimal actuator for a 5 m diameter scaled model of the Five-hundred-meter Aperture Spherical radio Telescope (FAST), followed by digital control experiments on the chosen actuator. Based on the optimal design scheme, an ARCS prototype is constructed, which accelerates project completion and substantially reduces trial-and-error costs.

Assessing the Critical Factors Leading to the Failure of the Industrial Pressure Relief Valve Through a Hybrid MCDM-FMEA Approach

Industrial pressure relief valves must function reliably and effectively to protect pressurized systems from excessive pressure conditions. These valves are essential safety devices that act as cushions to protect piping systems, equipment, and vessels from the risks of high pressure, which can cause damage or even explosions. The objectives of this study were to minimize valve failures, decrease the number of rejected valves in the production line, and enhance the overall quality of pressure relief valves. This work introduces an integrated quality improvement methodology known as the hybrid multi-criteria decision-making (MCDM)—failure mode and effects analysis (FMEA) approach. This approach is based on prioritizing crucial factors for any failure modes in the industrial setting. The presented case study demonstrates the application of a hybrid approach for identifying the fundamental causes of industrial pressure relief valve failure modes and malfunctions. This investigation highlights the applicability of FMEA as a methodology for determining causes and executing remedial actions to keep failures from happening again. FMEA helps uncover the underlying causes of industrial pressure relief valve failures, while the integration of the hybrid MCDM methodology enables the application of four integrated MCDM methods to identify crucial factors. The adopted model addresses the shortcomings of the conventional FMEA by accurately analyzing the relationships between the risk factors and by utilizing several MCDM methods to rank failure modes. Following the application of the adopted methodology, it was discovered that the high-risk failure modes for the pressure relief valve included misalignment of wire, normal wear/aging, rejection of machined parts, mismatch of mating parts, and corrosion. Therefore, risk managers should prioritize developing improvement strategies for these five failure modes. Similarly, failures comprising debris, delayed valve opening, internal leakage, premature valve opening, and burr foreign particles were determined as second essential groups for improvement.

Refined dimensional accuracy in FDM components via ensemble weight-optimized surrogates and hybrid NSGA-II-TOPSIS optimization

ABSTRACT In this paper, a novel approach was developed to predict the geometrical deviation and density of fused deposition modeling (FDM) parts and to optimize these outcomes by fine-tuning the relevant process variables. The prediction process utilized an ensemble approach, combining the optimized weighted sum of three individual surrogate models. These models correlate the input variables – nozzle temperature (NT), infill fraction (IF), and print speed (PS) – with the output responses of density, internal ovality (IO), and external ovality (EO). According to the results, the ensemble outperformed the individual surrogates, exhibiting enhanced predictive accuracy. Subsequently, non-dominated sorting genetic algorithm II (NSGA-II), a multi-objective optimization technique, was integrated with the technique for order of preference by similarity to ideal solution (TOPSIS), a multi-criteria decision-making method, to optimize the ensemble of surrogates (EoS) and generate a ranked set of Pareto-optimal solutions. The outcomes from the EoS, combined with the NSGA-II-TOPSIS hybrid optimization process, revealed that the most effective optimal control parameters were approximately 195°C for NT, 50% for IF, and a range of 55–66 mm/min for PS. This hybrid approach affirmed the reliability and robustness of the identified processing parameters for the production of top-quality FDM parts with desired dimensional accuracy and density.

Grey preferences selection index with trimmed group preference for evaluating university dormitory renovation design

Renovating old buildings is a strategic approach to resource optimization and sustainability. However, dormitory design decisions are often made by a limited panel of experts, which risks excluding student preferences-key to the design process. Expert assumptions about student needs can lead to biased outcomes, and attempts to gather student input may suffer from respondent bias and inconsistent engagement, introducing data noise. This paper presents the Grey Trimmed Preferences Selection Index (GTPSI) Multi-Criteria Decision Making (MCDM) method, an improved preference selection index MCDM method that integrates expert weights and refines student feedback by filtering outliers, using interval grey numbers to address uncertainty. Applied to dormitory renovation proposals, GTPSI provides a stable ranking framework, as confirmed by whitening sensitivity analysis, ensuring consistency across grey bounds. To further validate the selected alternative, results are cross-verified with TOPSIS and ELECTRE-III, reinforcing GTPSI’s robustness in aligning renovation designs with actual student needs. The GTPSI method thus offers a comprehensive solution for integrating user-centered preferences into expert evaluations, promoting designs that better meet stakeholder expectations.

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the Pareto-optimal solutions obtained by multi-objective optimization), where the performance of each alternative is quantified against several criteria (or objectives). This paper presents a comprehensive review of the application of MCDM methods in chemical and process engineering. It systematically outlines the essential steps in MCDM including the various normalization, weighting, and MCDM methods that are critical to decision making. The review draws on published papers identified through a search in the Scopus database, focusing on works by authors with more contributions to the field and on highly cited papers. Each selected paper was analyzed based on the MCDM, normalization, and weighting methods used. Additionally, this paper introduces two readily available programs for performing MCDM calculations. In short, it provides insights into the MCDM steps and methods, highlights their applications in chemical and process engineering, and discusses the challenges and prospects in this area.

BIM-based search and selection of construction material suppliers: a dedicated framework and prototype

Purpose This study aims to address the key issues concerning supplier selection in traditional construction procurement by proposing an innovative, novel, state-of-the-art prototype plugin building information modelling – supplier search and ranking (BIM-SSR) and an associated conceptual framework. It enhances building information modelling (BIM) capabilities through web crawling and analytical hierarchy processes (AHP). It uses the World Wide Web to procure construction material suppliers. Design/methodology/approach Prevalent issues in traditional procurement of material suppliers have been identified through a rigorous literature review. Field experts vetted these issues. A framework has been presented to address these issues based on integrated web crawling and AHP as a multi-criteria decision-making (MCDM) method. A BIM prototype (BIM-SSR) has been developed using Python and plugged into Autodesk Revit to automate the search and evaluation of material suppliers based on precise material specifications from the BIM design. The BIM-SSR prototype is tested through a case study and validated by field professionals for its efficiency in tackling the identified issues. Findings Thirteen key issues have been identified concerning traditional construction procurement pertinent to supplier selection. Best-value procurement was encouraged by identifying supplier selection criteria such as cost, delivery time, experience, compliance with quality management standards, warranties, and claim period. The presented BIM-SSR prototype has an efficiency of 80%–95% in addressing the issues identified in this study and 97.5% effectiveness in improving the overall procurement management process. Originality/value The BIM-SSR prototype developed in this study is a novel and innovative addition to the body of knowledge that has been integrated into Autodesk Revit as a Plugin. Automation of supplier search and selection through digital technologies, including web crawling and integration of traditionally accepted MCDM methods such as AHP in BIM, is another innovation in the current study. Overall, this study presents a holistic, innovative system, from conceptual design to practical implementation and demonstration. This is one of the steps to help the traditional construction procurement process evolve into a more modern and digital procurement.

Privacy Preferences of Consumer and Lender: A Case of Digital Credit Systems in India

Digital credit services are rapidly evolving in the Internet commerce environment. As such, this study aims to identify and prioritize the key factors influencing the views of digital credit users (DCU) and digital credit providers (DCP) on privacy practices. The study begins with a comprehensive literature review to identify an extensive set of factors and inputs from an expert panel. Next, the study applies the well-established “multi-criteria decision-making method,” which allows assigning weights to each of the four criteria and 13 sub-criterions to reveal DCU and DCP preferences for digital credit protection. Results indicated that the “Concerns about Personal Information” criteria are prioritized highly by DCU and DCP. This study marks the first attempt to reveal the preferences of DCU and DCP digital data privacy policies in a growing economy (India) and help policymakers and regulators align their digital privacy policies, enhancing the overall user experience.

Decision-Making Approach for Land Use in Urban Industrial Area Redevelopment Projects

The process of industrial transformation, becoming the most important for building up sustainable cities, is in urgent need for studying alternative options for land use to ensure sustainable city development. Rapid urbanization requires new built-up design in strong correlation with urban spatial planning issues. The objective of this paper is to contribute for the studies of sustainable land use solutions through investigating the problems of the reorganization of depressed industrial areas. The research methodology is based on the multicriteria decision-making method to provide primarily social functions of depressed industrial areas, depending on environmental and economic aspects of their historical location in urban structure. Since the article highlights the concept of the 15-min city to build a polycentric urban spatial structure, the assessment of supply and demand matching of social facilities is based on the analysis of 15 min accessibility to the serviced within either industrial zone and the city on the whole. The GIS spatial analysis method supports the developed criteria set to evaluate main city functions. The research provides the methodology for defining the priority land use solution for a specific industrial area in a specific location. The proposed methodology suggests a procedure for evaluating the importance of the land use composition for the city community, considering environmental requirements and cost-effectiveness of the project. Three different industrial zones located in the same city are a case study to asses the reliability of the proposed methodology. The research conclusion provides implementing sustainable land-use solutions for improving urban environment quality as well as the quality of life for the population.

Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from the Ele.me platform. Quantitative methods, including the frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze satisfaction differences between men and women riders. The findings reveal an asymmetric pattern in satisfaction preferences: women riders place more emphasis on perceived value, while men riders prioritize service perceived quality. Although both groups rank platform image, product perceived quality, and rider expectations similarly, the importance of these factors varies significantly, indicating an underlying asymmetry in their expectations and values. Women riders express higher satisfaction with platform image, rider expectations, service perceived quality, and product perceived quality, with rider expectations showing the largest difference. Additionally, the multi-criteria decision-making methods used in this study offer insights for optimizing service performance in real-time crowdsourcing logistics platforms, particularly in handling uncertainty and enhancing system adaptability through fuzzy sets. These findings provide a basis for developing gender-specific strategies aimed at enhancing rider satisfaction, minimizing turnover, and improving platform adaptability—contributing to a more inclusive and sustainable logistics supply chain.

Анализ и классификация многокритериальных методов принятия решений

Decision-making requires in-depth analysis through the evaluation and comparison of various alternative solutions. These tasks are characterized by multiple criteria used for comparison. The variability of parameters and conditions in decision-making has led to the development of numerous methods aimed at facilitating this process effectively. Currently, several hundred multi-criteria decision-making methods are known, making it challenging to select the most appropriate one for practical use. Therefore, research on the analysis, classification, and systematization of multi-criteria decision-making methods is relevant and essential for decision-makers and developers of decision support systems. Most classifications emphasize the methodologies and purposes of these methods, often overlooking their inherent limitations. This article attempts to systematize the main multi-criteria decision-making methods, considering their limitations. It analyzes the most widely used methods and their classifications. Based on identified limitations, the paper proposes a classification of multi-criteria decision-making methods and guidelines for selecting them. Applying this approach can enhance the validity of method selection and, consequently, the effectiveness of the decisions made.

Application of hybrid multi-criteria decision-making method to the evaluation of corporate social responsibility: An example of the banking industry in China

Corporate social responsibility (CSR) is a popular research topic, but there have not been comprehensive discussions on CSR evaluation in the banking sector. The purpose of this study is to propose a two-stage analysis combining the modified Delphi method (MDM) and Analytic Network Process (ANP) in order to construct a model for evaluating banks’ CSR. First, we use MDM to select and determine the interdependence of the criteria and then employ ANP to obtain their weights and to rank the alternatives. The results show that 5 criteria and 18 sub-criteria need to be considered in CSR evaluation. The most important criterion and sub-criterion are bank governance and regulatory compliance, respectively. The evaluation model constructed herein can be taken as a decision-making guide for evaluating banking organizations’ CSR and to help promote CSR development in China’s financial industry.

Интерактивное приложение, реализующее метод уверенных суждений на массовой программной платформе

The article examines the functionality and architecture of an interactive application designed to support multi-criteria decision-making using S.A. Piyavsky's confident judgment method. It provides a description of key components of this method essential for presenting the topic in a computer-oriented format for data and knowledge representation. The application stores and provides access to a bank of universal importance coefficients for specific criteria and serves as the core of an information methodology for decision-making based on the confident judgment method. This methodology includes the following stages: compiling a list of alternative solutions with evaluations by a set of specific quantitative criteria; establishing a selection policy that orders criteria by importance for the decision-maker; normalizing the multi-criteria problem statement in line with a foundational optimization model; evaluating each alternative solution within this model; and selecting the optimal alternatives. The application automatically coordinates the creation and editing of the list of alternative solutions according to variation boundaries set by the selection policy, integrating all solution stages with user feedback. The application’s functionality is represented by a diagram linking the main activities and their outcomes, along with a UML diagram of application use cases. The architecture of the application is presented as a mind map. The application is implemented on the Excel platform using VBA programming language, chosen to ensure accessibility and support the development of advanced multi-criteria decision-making methods for a broad user base who use Excel in their professional work.

Determining the effect levels of augmented decent work criteria in sustainable economic development with the fuzzy DEMATEL method

Creating decent work is among the priority issues for sustainable employment and development. This study aimed to determine the effect levels of the International Labour Organization (ILO) decent work criteria by augmenting nine indicators in the ILO manual to 12 criteria through a comprehensive literature review. Fuzzy DEMATEL, a multi-criteria decision-making method, has been preferred in this context. According to the analysis results of the study, the most heavily ranked criteria are ‘healthy workplace environment’, ‘decent working hours’ and ‘safe working conditions’ respectively, which contribute to the decent work concept. Further, ‘balance between work–family–personal life’ has been found the most affected criterion, while ‘education and training system’ has been the most affecting. Based on the findings, remedial and developing strategies are suggested on issues such as corporate culture, working hours regulation, safe working environment, subordinate–superior relations, social activities and regulations that take family life into account.

A Multicriteria Decision-Making Approach for Urban Water Features: Ecological Landscape Architecture Evaluation

In recent decades, the issues of ecology and environmental sustainability have become a global concern in contemporary urban design. Among various urban elements, water features play a significant role in improving the ecological characteristics of their surrounding environment, especially in hot and arid areas. The aim of this study is to evaluate the ecological characteristics of urban water features comprehensively and quantitatively, which has been overlooked in previous studies, taking their physical characteristics into account. To this end, a multicriteria decision-making method, an analytic network process, was proposed to quantitatively evaluate the ecological characteristics of water features. In this approach, four ecological criteria—microclimate, biodiversity, greenery, and human wellbeing—and ten physical characteristics of water features were considered. Twenty-one experts were asked to complete a questionnaire for pairwise comparisons of all ecological criteria and the influence of physical characteristics. The results showed that vegetation and scale, with the relative influencing values of 0.255 and 0.188, respectively, were identified as the most decisive features influencing ecological criteria. Conversely, texture, with a value 0.023, had the least impact. Moreover, it was shown that water features have the greatest impact on the microclimate compared with other ecological criteria. The results were used to compare water features at the Koohsangi Transregional Park, located in a hot and arid city of Iran. The results of this study lead to a framework that can help urban designers integrate ecological criteria into water feature planning to enhance urban ecology and sustainability.

Navigating Decision Making with Generalized Temporal Intuitionistic Fuzzy Sets and Soft Sets

The study addresses the challenges posed by evolving data within generalized intuitionistic fuzzy sets. Traditional methods often fall short in handling such complexity. To overcome this, we introduce the concept of a generalized temporal intuitionistic fuzzy set, extending the traditional framework to incorporate temporal dynamics. Additionally, we define a generalized temporal intuitionistic fuzzy soft set, integrating temporal aspects into the soft set framework. Recognizing the need for advanced operations like union and intersection to merge opinions across different periods, we propose practical solutions for decision-making in this dynamic context. Two novel multi-criteria decision-making methods are introduced, specifically designed to address decision-making problems within generalized temporal intuitionistic fuzzy soft sets. We develop Scilab codes for these methods, enabling the creation of a multiple-input single-output system. This system is applied to complex real-life examples, involving numerous parameters, time moments, and decision-makers. This comprehensive approach aims to provide robust tools and methodologies for decision-making processes amidst the intricate dynamics of temporal data within the framework of generalized temporal intuitionistic fuzzy sets.

Navigating Decision Making with Generalized Temporal Intuitionistic Fuzzy Sets and Soft Sets

The study addresses the challenges posed by evolving data within generalized intuitionistic fuzzy sets. Traditional methods often fall short in handling such complexity. To overcome this, we introduce the concept of a generalized temporal intuitionistic fuzzy set, extending the traditional framework to incorporate temporal dynamics. Additionally, we define a generalized temporal intuitionistic fuzzy soft set, integrating temporal aspects into the soft set framework. Recognizing the need for advanced operations like union and intersection to merge opinions across different periods, we propose practical solutions for decision-making in this dynamic context. Two novel multi-criteria decision-making methods are introduced, specifically designed to address decision-making problems within generalized temporal intuitionistic fuzzy soft sets. We develop Scilab codes for these methods, enabling the creation of a multiple-input single-output system. This system is applied to complex real-life examples, involving numerous parameters, time moments, and decision-makers. This comprehensive approach aims to provide robust tools and methodologies for decision-making processes amidst the intricate dynamics of temporal data within the framework of generalized temporal intuitionistic fuzzy sets.

Evaluation of OECD Countries in Terms of Better Life Index According to Bulut Index

Background: The "Better Life Index", first developed by the Organization for Economic Co-operation and Development (OECD) in 2011, includes many criteria from the functioning of public services to environmental wealth, from security services to individual and social well-being. Method: The performances of OECD countries according to the decision criteria that constitute the Better Life Index has been evaluated with Bulut Index (BI) method, which is a multi-criteria decision-making method. Normalized Maximum Values (NMV) method, one of the objective weighting methods, was used to determine weights of decision criteria. Findings: Among the indicators of the Better Life Index, the murder rate per 100 thousand population ranks first in terms of criterion weight. In the study, due to the analysis and evaluation made with Bulut Index, Switzerland ranked first among OECD countries with 82.28 points in the welfare and well-being index ranking. On the other hand, Türkiye ranked fourth from the bottom among OECD countries. Conclusion: Based on the findings of the study, it is recommended that urgent and necessary measures be taken on homicide rates, long-term unemployment rates and air pollution criteria. The lack of criteria regarding civic participation, work-life balance and income status constitute limitations of the study. In future studies, it is especially recommended that other researchers include these variables.