Multi-criteria Decision-making Approach Research Articles

Multi-objective model for designing hydrogen refueling station powered using on-grid photovoltaic-wind system

This study formulated a multi-objective model to size a sustainable hydrogen refueling station energized by integrated Photovoltaic-wind system connected to grid. The model takes into account practical constraints alongside three objective functions: maximization of renewable energy fraction, minimization of overall costs, and minimization of greenhouse gas emissions. An exact algorithm is employed to obtain the best solution, and a multi-criteria decision-making approach is utilized to choose the optimal solution from Pareto-optimal solutions. The performance of the model is validated on a hydrogen station that fulfills the daily hydrogen requirements for a fleet of 100 taxis in Tabuk city, Saudi Arabia. Different scenarios are analyzed to demonstrate the trade-offs between the three objectives. For example, the first configuration consists of 6527 photovoltaic panels and 296 wind turbines with capacities of 2.219 MW and 0.888 MW, respectively. The energy deficit is covered by the grid and the excess is exported to the grid. The economic assessment of this configuration reveals a hydrogen cost of 7.53 $/kg. Additionally, this study considered a scenario of powering the station using off-grid Photovoltaic-wind battery system. This analysis explores these differences, focusing on cost-effectiveness and environmental implications of using renewable energy for hydrogen production.

Thermal Comfort–Based Differential Pricing for High-Rise Apartments in Hot and Humid Climates: A Multicriteria Decision-Making Approach

Thermal Comfort–Based Differential Pricing for High-Rise Apartments in Hot and Humid Climates: A Multicriteria Decision-Making Approach

Optimum selection of nature-inspired texture pattern for cutting tool surface using an integrated multi-criteria decision-making approach: a comparative analysis

Purpose This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface. Design/methodology/approach The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects. Findings The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface. Research limitations/implications Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces. Practical implications The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools. Social implications Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration. Originality/value Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

Application of the Analytic Network Process for Sub-Watershed Prioritization in the Huehuetan River Basin, Chiapas, Mexico

Sub-watershed prioritization is essential for developing watershed management plans that maximize impact with minimal resources. This study used a multicriteria decision-making approach to rank sub-watersheds by degradation status in the Huehuetan River Basin, Chiapas, Mexico. The eight sub-watersheds in the basin were classified using the Analytic Network Process (ANP) model, evaluating morphometry, hydrology, hillslope stability, soil water saturation, land-use change, and socioeconomic factors. The results identified hydrology and land-use change as the most influential criteria, with weights of 20.62% and 19.82%, respectively, driven mainly by surface runoff and deforestation. Swtr 08 and Swtr 07 were identified as the highest-priority sub-watersheds, covering 24.31% of the basin area, with 55.31% of Swtr 08 classified as unstable and showing a combined high-vegetation loss of 16.46 km2. The entire watershed showed an annual vegetation loss rate of 146 ha year−1. Increasing the weighting by 50% resulted in greater variability in priority rankings, with runoff and low vegetation showing maximum global ranges of −44.33% and 30.25%, respectively, instability decreasing by 33.94%, and peak flow increasing by 18.20%. These findings emphasize the need for focused interventions in the vulnerable subwatersheds of the upper basin to manage runoff, curb deforestation, and reduce soil instability.

Surface metamorphosis techniques for sustainable polymers: Optimizing material performance and environmental impact

The transition to sustainable polymers is crucial for reducing the environmental footprint of additive manufacturing, particularly in fused deposition modeling (FDM). This study investigates surface metamorphosis techniques—methods to modify polymer surfaces at micro and nanoscale levels to enhance performance and minimize environmental impact. We explore plasma treatment, chemical etching, and laser texturing on biodegradable and recycled polymers, assessing their effects on surface properties, such as adhesion, roughness, and chemical resistance. Our results demonstrate significant enhancements in mechanical properties. For example, PLA’s tensile strength increased from 55.3 MPa (untreated) to 63.8 MPa (plasma treated), and its elongation improved from 4.2% to 5.1%. PHA showed a similar trend, with tensile strength rising from 45.1 MPa to 52.6 MPa, and elongation increasing from 5.6% to 6.4%. rPET and rPP also exhibited improvements, indicating the effectiveness of these surface treatments. Employing a multi-criteria decision-making approach, we assess and prioritize these techniques based on their mechanical enhancements and sustainability profiles. While this study presents hypothetical results, it establishes a comprehensive framework for optimizing surface metamorphosis processes, guiding future experimental research. Our findings suggest that tailored surface modifications can significantly improve the performance and environmental sustainability of polymers in FDM, offering pathways for integrating eco-friendly materials into advanced manufacturing. This work contributes to the development of green manufacturing technologies by highlighting surface metamorphosis as a key strategy for achieving high-performance and sustainable materials.

Climate-Driven Sustainable Energy Investments: Key Decision Factors for a Low-Carbon Transition Using a Multi-Criteria Approach

Currently, the need for a clean transition has made the upscaling of sustainable energy investment projects imperative. This paper addresses the increasing importance of sustainable energy investment projects in the context of climate change and the urgent need for a global energy transition. Given the complexity of decision-making in this field, a multi-criteria decision-making (MCDM) approach is employed to assess the main criteria considered by project developers and financial institutions. Using the Analytic Hierarchy Process (AHP) method, eight criteria are identified and evaluated. Results highlight differing priorities between project developers and investors, emphasizing the need for adaptable approaches to accelerate sustainable energy investments. The study underscores the importance of understanding diverse stakeholder preferences and priorities in formulating effective strategies and managing associated risks to effectively promote sustainable energy projects. Future research should focus on real-life case studies and policy assessments to further enhance the understanding of sustainable energy investment dynamics.

A new Fermatean fuzzy Spearman-like correlation coefficient and its application in evaluating insecurity problem via multi-criteria decision-making approach

A new Fermatean fuzzy Spearman-like correlation coefficient and its application in evaluating insecurity problem via multi-criteria decision-making approach

Setting priorities for police operations by using a multicriteria decision approach with partial information

Abstract The paper presents a real-world decision-making problem in the context of the Brazilian Federal Police (BFP), which consists of establishing priorities for Police Operations. This study deals with allocating resources to trigger police operations that, while demanding more resources and specialized techniques, also promote the effectiveness of police actions more conspicuously and directly. Driven by the Value Focused Thinking methodology, the objectives and values of the Federal Police were structured and represented by criteria, which let police operations be evaluated and prioritized. The FITradeoff method was applied to rank the operations, with an innovative methodological perspective, which integrates two different paradigms for preference modelling: elicitation by decomposition and holistic evaluations. A mathematical modelling approach is presented to deal with the combination of both types of information obtained by the Decision Maker (DM), in order to search for dominance relations between alternatives. This study shows how incorporating holistic judgments in the process can be useful for tightening the decision process, since the inequalities obtained with holistic judgments have a high impact on the space of weights compatible with the DM’s preferences. A clear conceptual framework is presented for the analysis, showing how the application of such a combined approach to prioritizing special police operations adds a step to the decision-making processes and policies of the BFP, thereby broadening the managerial implications of tackling public security issues by seeking to solve them using management mathematics.

Prediction of eco sustainability component using fuzzy Z numbers based ratio analysis and interval type 3 fuzzy logic system

Amid rapid global urbanization, understanding eco-sustainability challenges in megacities like Delhi is crucial both locally and globally. This study introduces a novel multi-criteria group decision-making approach, the Z-Fuzzy Step-Wise Weight Assessment Ratio Analysis (SWARA), to address these complex challenges. This method prioritizes key eco-sustainability components like air quality index (AQI), water quality index (WQI), Temperature, and Precipitation, based on their impact, aiming to enhance resource allocation and environmental quality. Criteria weights are determined using fuzzy analytical hierarchical processing with Z-numbers, which manage decision-makers' uncertainty through a reliability function, illustrating their confidence levels and supporting the adaptability and effectiveness of eco-sustainability measures. A case study is conducted on seven sub-cities in Delhi examining their unique environmental impacts and urban sustainability challenges. Moreover, the most effective component of eco-sustainability say AQI is also dependent on some factors like PM10, PM2.5, SO2, O3, NO2, and CO. Considering these factors as inputs, an interval type-3 fuzzy logic system (IT3FLS) has been constructed to predict AQI, supporting timely interventions and improvements in eco-sustainability management. The IT3FLS model demonstrated exceptional precision across all Delhi sub-cities, with low root means square error (<0.05), and high R2 values (>0.94), affirming its effectiveness. To validate the Z-Fuzzy SWARA rankings, we compared them with existing Z-Fuzzy methods, consistently ranking AQI first. The IT3FLS's AQI predictions were also compared with those from fuzzy logic and advanced machine learning algorithms, demonstrating superior performance. Finally, the study underscores the managerial implications, emphasizing their role in guiding decision-making and strategy implementation.

Application of Multi-criteria Decision-making Methods for Forensic Analysis of Mechanical Parts in Vehicle Accidents using q-Rung Orthopair Fuzzy Numbers

This study explores the application of a Multi-Criteria Decision-Making (MCDM) approach based on q-rung orthopair fuzzy numbers to identify the origin of mechanical parts found at vehicle accident scenes. The primary objective is to determine the most likely vehicle to which these parts belong by evaluating key criteria such as compatibility, damage level, serial number matching, and color compatibility. Q-rung orthopair fuzzy numbers offer an advanced method to handle the inherent uncertainty and vagueness associated with forensic evaluations, particularly in scenarios where data is incomplete or imprecise. The proposed methodology involves defining the criteria, assigning membership and non-membership degrees using q-rung orthopair fuzzy sets, and applying an aggregation process to effectively rank alternatives. This approach facilitates flexible decision-making by accommodating different levels of confidence and uncertainty, making it particularly suitable for forensic applications where evidence is often ambiguous. The findings demonstrate that integrating q-rung orthopair fuzzy numbers into the MCDM framework significantly enhances the accuracy and reliability of identifying vehicle components involved in accidents. The proposed methodology provides a systematic tool to support forensic investigations, aiding in the determination of liability and contributing to more robust outcomes in mechanical evidence analysis.

Evaluation of sustainable hydrogen production technologies by fuzzy AHP analysis with bootstrapping

The concept of a hydrogen economy has received increasing attention worldwide. Hydrogen is a promising energy carrier that contributes to the development of a sustainable and reliable energy sector. Selection of the most sustainable hydrogen production technology (HPT) plays a significant role in promoting a hydrogen economy. However, it is regarded as a multi-criteria decision-making (MCDM) problem with several incompatible evaluation criteria. In this study, we develop an MCDM approach based on Fuzzy Analytic Hierarchy Process (FAHP) for prioritizing HPT alternatives, focusing on Egypt as a case study. Our contributions are twofold. First, to combat the issue of a small number of subject matter experts, a bootstrap method is employed to validate the main criteria weights in FAHP. Second, we conduct a comparative FAHP analysis from a broad perspective of the national experts from a developing country and the international experts from developed countries. Our results show that PV electrolysis is the most preferable technology option from the perspectives of both the national and international experts. Since the FAHP approach proposed is a flexible framework that can be applied to countries other than Egypt, it will support global policymakers and industry stakeholders in their decision making toward a sustainable and efficient hydrogen economy strategy.

An Extension of VIKOR Approach for MCDM Using Bipolar Fuzzy Preference δ-Covering Based Bipolar Fuzzy Rough Set Model

Bipolarity highlights the positive and negative facets of a certain dilemma. This script aims to propose a novel multi-criteria decision-making (MCDM) approach based on bipolar fuzzy preference δ-covering based bipolar fuzzy rough set (BFPδC-BFRS) model by combining the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Rasenje) scheme. The VIKOR scheme is viewed as a beneficial MCDM strategy, particularly in situations where an expert is incapable of making the right decision at the beginning of system design. The VIKOR method works well for problems with competing attributes because it operates under the presumptions that compromise is acceptable in conflict resolution, the expert seeks a solution that is extremely close to the best, and all developed attributes are taken into consideration when processing the various alternatives. In this study, firstly, we proposed an integrated MCDM based on BFPδC-BFRSs using the VIKOR methodology. Moreover, we solve a real-world illustration to show the effectiveness of the expanded VIKOR approach. Finally, we demonstrate a detailed comparative analysis of the proposed methodology with some prevalent decision-making approaches to substantiate the accountability of the recommended scheme.

A Comprehensive Approach for Selecting Third-Party Logistics Providers

The finest third-party logistics (3PL) supplier is a vital decision for businesses trying to streamline their supply chain operations. In order to free up time for businesses to concentrate on their core skills, third-party logistics providers offer a variety of services, such as distribution management, warehousing, and transportation. However, selecting the best 3PL supplier necessitates a rigorous assessment of variables including sector expertise, technical prowess, service quality, scalability, and cost-effectiveness. This introduction discusses the significance of choosing the best 3PL supplier and emphasizes important factors to take into account when making a choice. It is essential since there is a chance that third-party logistics (3PL) provider selection study may boost the supply chain's effectiveness and competitiveness. Firms may make selections that are tailored to their unique requirements by recognizing and assessing the elements that affect the choosing process. Proper 3PL selection may boost market response, save costs, expand the capacity of operations, and improve customer happiness. As a result, research in this field helps to create best practices and strategies that enhance supply chain management and promote entrepreneurship. A multi-criteria decision-making approach called The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank and choose the best option from a list of options. To determine how closely each alternative resembles the ideal answer, TOPSIS takes into account both positive and negative features. Based on the greatest distance from the inverse idealistic and the lowest distance to the positive ideal, the outcome score is calculated. This approach facilitates decision-making processes in a variety of contexts, such as project prioritization, supplier selection, and investment appraisal. Alternative parameters taken as 3PL-1, 3PL-2, 3PL-3, 3PL-4, 3PL-5. Evaluation parameters taken as Delivery Service (%), Quality of the Customer Experience (Quos), Coverage of the EU Territories (%), Flexibility, and Cost (EUR/km). From the result it is seen that 3PL-2 secures the first rank which is acquired by the TOPSIS method. To secure the first place on the table consistency will be the key factor which was maintained by 3PL-2

Enhancing Urban Mobility with Aerial Ropeway Transit (ART): Future Accessibility Impacts of Multimodal Transit Expansion Scenarios

Aerial ropeway transit (ART) systems are emerging alternatives to augment existing transit systems in congested cities in the Global South, especially in urban areas with limited transit coverage because of road width constraints or topography. Integration of aerial cable car stations to an existing transit network can improve the overall accessibility of various population segments with significant positive benefits in relation to reducing transport-related social exclusion. This study evaluated the impact of introducing ART in the city of Varanasi (India) and assessed the spatial accessibility improvements to critical facility locations such as heritage sites, educational institutions, hospitals, and employment centers. Several multimodal transit expansion scenarios were considered in this study and the potential benefits of each case were quantified using the two-step floating catchment area (2SFCA) method. A multi-criteria decision-making (MCDM) approach was subsequently employed for identifying the optimal locations of ART stops. Microlevel analysis findings suggest that the mean accessibility values could increase up to 10.92% in the first phase of the ART implementation, which could subsequently increase to 24.7% and 49.8% for the subsequent transit expansion scenarios. The study also investigated the Varanasi ART DPR prepared by Varanasi Development Authority (VDA) and showed that a significant increase of 16% in accessibility levels could be achieved if optimal stop locations identified in this study were implemented. The proposed two-step (2SFCA+MCDM) method for identifying the optimal locations of ART stations in a multimodal transit network is expected to be an effective tool for transit system redesign using place-based accessibility measures.

Exploration of Sustainable Potential Sports Tourism in Sumedang, Indonesia Using Multi-Criteria Decision-Making

Objective: This research aims to explore sports tourism, which has the greatest potential for the development of sports tourism, economic quality, regional image and human resources Theoretical Framework: Sport Tourism is a form of special interest tourism in the world of tourism and is widely developed in various regions because it can encourage tourists to visit. Method: The method used in this research is the qualitative method, a Multi-criteria decision-making (MCDM) approach withusing the Analytic Hierarchy Process (AHP) method to determine potential sport tourism. Criteria AHP using the concepts of Marketability, Sustainability, Participation, and Disaster Mitigation (MSPDM). Results and Discussion: The results of this research, based on the Analytic Hierarchy Process (AHP) analysis utilizing the MSPDM indicator, the three most promising sports tourism activities among the eight currently operating in Sumedang were identified: paragliding, golf, and rafting. Among these top contenders, paragliding and rafting emerged as priorities for further development. While golf also holds potential, it is managed by a private company, which might limit its reliance on government funding due to its own revenue streams from the resort business. Research Implications: The implications of this research are discussed. The ranking of potential sports tourism activities provides valuable insights for the government in determining which areas to prioritize for development. Originality/Value: This study use A multi-criteria decision-making (MCDM) approach, employing the Analytic Hierarchy Process (AHP) method, was utilized to assess the potential of various sports tourism activities. The AHP criteria were based on the concepts of MSPDM.

Health Insurance Provider Selection Through Novel Correlation Measure of Neutrosophic Sets Using TOPSIS

Risk monitoring aims to recognize and control potential threats to our assets or health activities. Insurance is vital, as it compensates for any unexpected loss of property or life. Clients selecting the best health insurance provider must consider various factors and their relative significance to their circumstances. Multi-criteria decision-making (MCDM) helps people analyze and compare policy alternatives to find the best option. This research aims to assist potential health policy purchasers by addressing the selection of health insurance providers as an MCDM problem. The correlation coefficient is useful for identifying the importance of several conflicting criteria. The idea of correlation coefficients is extended in a neutrosophic context to capture the indeterminacy and incomplete information in the relationship among the criteria. The technique for order preference by similarity to an ideal solution (TOPSIS) approach is a useful and straightforward approach to solving MCDM problems. However, it often became ambiguous to researchers due to its involvement in the distance measure technique. The proposed neutrosophic correlation measure may also replace the ambiguity of using a suitable distance measure in the TOPSIS approach. This study extends the TOPSIS method by using the proposed neutrosophic correlation coefficient on single-valued neutrosophic sets (SVNSs). The criteria preferences are computed using a method based on the removal effects of the criteria (MEREC) approach. Some valuable concepts, like the weighted closeness measure of type I and type II and the weighted index parameter, are introduced with their properties to establish the proposed neutrosophic TOPSIS approach. An MCDM approach for health insurance providers has been constructed to illustrate the proposed approach numerically. The proposed method suggest that the health insurance provider ϒ2 is the most beneficial alternative, whereas ϒ1 is the least suitable. The client considers the terms and conditions for non-coverage and the facilities provided for pediatric and maternity care while buying health insurance. The comparative analysis of the suggested technique demonstrates the merit of the research in terms of consistency. The sensitivity analysis demonstrates the flexibility and robustness of the obtained results.

Decoding organisational attractiveness: a fuzzy multi-criteria decision-making approach

Decoding organisational attractiveness: a fuzzy multi-criteria decision-making approach

Optimizing green hydrogen strategies in Tunisia: A combined SWOT-MCDM approach

Tunisia's rapid industrial expansion and population growth have created a pressing energy deficit, despite the country's significant, yet largely untapped, renewable energy potential. This study addressed this challenge by developing a comprehensive framework to identify and evaluate strategies for promoting green hydrogen production from renewable energy sources in Tunisia. A Strength, Weakness, Opportunity, and Threat (SWOT) analysis, incorporating social, economic, and environmental dimensions, was conducted to formulate potential solutions. The Step-wise Weight Assessment Ratio Analysis (SWARA) method facilitated the weighting of SWOT factors and sub-factors. Subsequently, a multi-criteria decision-making approach, employing the gray technique for order preference by similarity to ideal solution (TOPSIS-G) method (validated by gray additive ratio assessment (ARAS-G), gray complex proportional assessment (COPRAS-G), and gray multi-objective optimization by ratio analysis (MOORA-G), was used to rank the identified strategies.The SWOT analysis revealed "Strengths" as the most influential factor with a relative weight of 47.3 %, followed by "Weaknesses" (26.5 %), "Threats" (15.6 %), and "Opportunities" (10.6 %). Specifically, experts emphasized Tunisia's renewable energy potential (21.89 %) and robust power system (12.11 %) as primary strengths. Conversely, high investment costs (11.2 %) and political instability (7.77 %) posed substantial threat. Positive socio-economic impacts represented a key opportunity with a score of 5.2 %. As for the strategies prioritizing criteria, production cost ranked first with a score of 13.5 %, followed by environmental impact (12.8 %), renewable energy potential (12.0 %), and mitigation costs (11.3 %). The gray TOPSIS analysis identified two key strategies: leveraging Tunisia's wind and solar resources and fostering regional cooperation for project implementation. The robustness of these strategies is confirmed by the strong correlation between TOPSIS-G, ARAS-G, COPRAS-G, and MOORA-G results. Overall, the study provides a comprehensive roadmap and expert-informed decision-support tools, offering valuable insights for policymakers, investors, and stakeholders in Tunisia and other emerging economies facing similar energy challenges.

Aerodynamic performance characteristics of low Re airfoils: A parametric and multi criteria decision study

This research aims at investigating the aerodynamic performance of 51 low Re airfoils and applying a Multi Criteria Decision Making (MCDM) approach for selecting airfoils that align with the specific requirements of small wind turbines (SWTs). The study was carried out by varying the Re from 5 × 104 to 5 × 105; angle of attack (AOA) from −10° to 20°, thickness to chord ratio (0.1–0.9), camber ratio (0.1–0.9), and camber position (10 %–80 %) to evaluate the impact of these parameters on the airfoils’ performance. Furthermore, MCDM approach was applied to identify suitable airfoils optimized for their average lift to drag ratio, stall angle, operating range of AOA, strength, manufacturability, and material cost. The findings showed that of the teste parameters, the AOA and airfoil profile have the most pronounced effects on the airfoil performance. Among the tested airfoils, the E63 provided superior performance at 105 Re with LDR of 76.32, a 37.7 % improvement over that of NACA 4412 which is commonly used for wind turbine blade design. Furthermore, the MCDM results revealed that SG6043, FX63-137, E216 and E62 airfoils were the top-ranked airfoils suitable for SWTs application. These findings can help to produce optimized airfoil designs for increased performance and efficiency of SWTs.

Performance Analysis of Indian Railway Zones using MCDM Approaches

The study aims to enhance the efficiency and effectiveness of Indian Railways (IR), a public sector infrastructural organization, through a performance analysis using various Multi-Criteria Decision-Making (MCDM) methods. Analyzing the Indian Railway’s open data, the study optimizes and ranks the zones of IR, offering insights for targeted investments to boost future performance. This research holds value by furnishing managerial perspectives, formulating strategies, and elevating the performance of different zones within Indian Railways. Through the identification of improvement areas, the analysis empowers decision-making, facilitating overall enhanced performance. MCDM, Indian Railways, Supply and demand, Data analysis.