Multi-criteria Decision-making Approach Research Articles

Sustainable cycle-tourism for society: Integrating multi-criteria decision-making and land use approaches for route selection

Cycle tourism is a sustainable active vacation, which is quickly growing in recent years. Although it has several benefits for society and users (e.g., social connections, amusement, and physical and mental health), cycle tourism requires an adequate route network to enjoy destinations with historical and landscape peculiarities. Past literature mainly investigated motivations and preferences for cycle tourists and proposed optimisation methods in planning routes. However, applying assessment methods for prioritising cycle-tourist routes is a seldom-explored topic. This study aims to address this gap by applying an integrated method for evaluating and prioritising cycle routes, searching for a compromise between route characteristics, service provided to users, and natural and building contexts crossed. It jointly includes Multi-Criteria Decision Methods (MCDMs) and a land use approach: AHP determines the weights of criteria and parameters describing cycle routes; GIS elaborates spatial analysis of parameters; ELECTRE I and VIKOR help find a compromise solution amongst different cycle routes. The integrated method involved a panel of experts to collect data, and it is applied to the wide-study area of Franciacorta (Italy). Some comparisons with other MCDMs are made to justify the results. The findings could support multi-institutions prioritising cycle route alternatives in deciding their building.

Determining the Suitability of Lands for Agricultural Use with the Best-Worst Method

The interaction of agricultural activities with the land starts with soil in the production part and continues until the consumption stage. Sustainable agricultural land for their use, a database regarding their current potential should be created and the land prepared based on this database should be evaluated by considering the use planning. The suitability of Ankara province lands for agricultural use by making use of the Geographical Information System analysis was carried out. To determine the suitability for agricultural use; Major Soil Groups, Land Use Capability Classes, soil depth, degree of erosion, elevation, slope, aspect, precipitation, and temperature criteria were used. This was done with the Best-Worst method, which is one of the multi-criteria decision-making approaches. It was ensured that the best and worst of the nine factors were determined by the decision makers. In the last layer, because of the analyzes made for the province of Ankara, the most appropriate land use map was created based on the natural abilities and capabilities of the lands. It has been determined that the most affecting criterion is Large Soil Groups, and Ankara's Kızılcahamam, Çankaya and Mamak districts are not very suitable for agricultural use, but other districts are generally suitable for use.

Prioritisation of operations during emergency shutdown of a crude distillation unit by interval-valued intuitionistic fuzzy analytic hierarchy process

A very reliable control system for offering a safety layer in emergency scenarios is an emergency shutdown system, or ESD system. It aids in preventing crises from having disastrous effects on the economy, the environment or business operations. In any plant, emergency shutdown systems reduce the risk of harm to the working population, the environment or equipment damage by guarding against leaks, hydrocarbon escapes, fire outbreaks and explosions. The ESD system halts process activity in an emergency, ensures that the hazard is isolated and does not worsen. It is essential that there is a clearly defined emergency procedure in place when a facility needs to be shut down in an emergency. When preparing an emergency procedure for use in an emergency, it is crucial to prioritise the operations. The factory uses an Interval-valued Intuitionistic Fuzzy Analytical Hierarchy Process (IVIFAHP) to prioritise activities in emergency situations. It is possible to design emergency shutdown systems using the aforementioned order of operations. It is possible to properly set up safety measures using the multi-criteria decision-making approach (MCDM). The Analytical Hierarchy Process (AHP) compares variables without taking measurement scales or units into consideration, which is a distinct benefit. The AHP’s handling of ambiguity, uncertainty and imprecise data is improved by the IVIFAHP.

An Integrated Fuzzy MCDM and Trend Analysis Approach for Financial Performance Evaluation of Energy Companies in Borsa Istanbul Sustainability Index

Financial performance evaluation is a great importance for companies. The aim of this study is to analyze the financial performances of energy companies traded in the Borsa Istanbul Sustainability Index in Turkey comparatively using trend analysis and multi-criteria decision making (MCDM). For this purpose, the changing values of accounting-based performance indicators over the years have been compiled from financial reports. The data were first evaluated by it was analyzed by Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HFTOPSIS). Then, it was analyzed by trend analysis for each variable separately. Comparative results show that MCDM rankings based on fuzzy set theory are different from analyzes performed alone. In addition, there is no study in the literature examining the financial performance of energy companies in Turkey based on the sustainability index.

Supply chain performance: a novel integrated decision-making model

PurposeKnowledge management (KM) significantly affects supply chain management (SCM) and its performance in today's highly competitive corporate climate. It is crucial to consider this relationship to achieve optimal supply chain performance (SCP). This study aims to assess this impact by defining and examining the multi-dimensional relationships between KM Process Elements (KMPEs) and SCP Evaluation Criteria (SCPEC) within a comprehensive theoretical framework.Design/methodology/approachIntegrating KMPEs and SCPEC becomes an uncertain decision-making problem due to data deficiency and the vagueness of decision-makers’ judgments. To address uncertainties, this study uses interval-valued neutrosophic (IVN) sets and proposes an IVN model consisting of SWARA, which is one of the effective multi-criteria decision-making (MCDM) approaches, and house of quality (HOQ) methods. IVN-SWARA is used to weight the SCPEC while IVN-HOQ establishes relationships and prioritizes the KMPEs and SCPEC.FindingsThe results show that reliability is the most significant SCP evaluation criterion. Among the KMPEs, capitalization, sharing, and transfer exhibit stronger associations with the SCPEC compared to the other elements. Capitalization as one of the KMPEs was found to be the most critical one, and efficiency is the criterion most affected by all elements of the KM process.Originality/valueThis study uses innovative methodologies to evaluate the adoption of KM processes on SCP under uncertain environments and involving multi-decision-makers. The proposed integrated model demonstrates flexibility and practicality in combining KM and SCM, leading to improved SCP. Notably, this study presents the development of IVN-SWARA and the use of the integrated IVN-SWARA - IVN-HOQ decision tool, which are novel contributions to the existing literature.

Solar Panel Cooling System Evaluation: Visual PROMETHEE Multi-Criteria Decision-Making Approach

The energy sector is interested in sustainable solar power plants. It is obvious that the working temperature of solar panels, which is significantly higher than the specified working cell temperature in hot climes, has a significant impact on efficiency and longevity. The selection of solar panel cooling systems, on the other hand, is worrisome since the choice process incorporates ergonomic, technical, economic, and environmental issues. The goal of this research is to (1) present a multi-criteria decision-making approach that is both quantitative and qualitative in nature for selecting solar panel cooling systems; (2) outrank nine alternative solar panel cooling systems with eleven performance measures for each alternative to assist decision makers in determining the best viable choice; and (3) visualize the relationship between the different solar panel cooling systems and performance measures under consideration. The proposed approach is to compare and rank solar panel cooling systems, as well as their validation and evaluation through sensitivity analysis. When operating efficiency is prioritized, finned air cooling is shown to be the best solar panel cooling technique, whereas thermosiphon cooling is the best alternative when emission reduction criteria are prioritized. A comparison of the findings shows that phase change material cooling and forced convection cooling performed worst in almost all cases.

Estimation of the Coastal Vulnerability Index Using Multi-Criteria Decision Making: The Coastal Social–Ecological System of Rachgoun, Western Algeria

This research deals with spatial vulnerability in the coastal area of Rachgoun (Algeria), on the southern shore of the Mediterranean Sea. Over the past two decades, the coastal area of Rachgoun has been suffering from a large amount of pressure due to accelerated socioeconomic development, urbanization, tourism, fishing, and agriculture. The main objective of this study is to visualize the coastal vulnerability of Rachgoun using multi-criteria decision making (MCDM). A multidisciplinary approach that integrates geological, physical, and socioeconomic vulnerability was adopted. The selected parameters for the study include lithology, elevation, slope, shoreline change, significant wave height, population density, tourist density, land use/land cover (LULC), road network density, proximity to coast, distance from river, people’s awareness, and designated conservation areas and cultural heritage. Data from AlSat-2 Satellite imagery, aerial photography, topographic maps, and field surveys were processed. Spatial modeling was conducted through the MCDM approach and geographic information systems (GIS) to develop two sub-indices: the natural vulnerability index (CVIN) and the socioeconomic vulnerability index (CVIS). The combination of the two sub-indices allowed us to deduce the integrated coastal vulnerability index (ICVI). The outcomes present a coastal vulnerability map with a spatial resolution of 10 m of the identified problematic area. This map can guide decision-makers in implementing an effective integrated coastal zone management (ICZM) strategy.

Which information locations in covered entities under HIPAA must be secured first? A multi-criteria decision-making approach.

Creating adequate safeguards for physical and online locations (e.g., desktop computers, network servers) where protected health information (PHI) may be breached is critical for management within entities compliant with the Health Information Portability and Accountability Act (HIPAA). With the increasing complexity of cyber breaches and budgetary issues, prioritizing which locations require the most immediate attention by top management through a data-driven model is more important than ever. Using CORAS threat modeling and five methods for multi-criteria decision-making, these locations were ranked from greatest to least risk of data breaches. Statistical methods were subsequently used for consistency and robustness checks. The findings illustrate that each type of covered entity under HIPAA must prioritize a different set of locations to safeguard first: health care providers must focus on the security of network servers, other portable electronic devices, and category of others (i.e., miscellaneous locations); health plans must focus on the security of paper and films, network servers, and others; and business associates must focus on the security of category of others, network servers, and other portable electronic devices. Combined with data on the source of the breaches (external vs. internal) and type of threats (e.g., hacking, theft), these findings provide recommendations for risk identification for privacy officers across health care.

An Interactive Multi-Criteria Decision-Making Approach for Autonomous Vehicles and Distributed Resources Based on Logistic Systems: Challenges for a Sustainable Future

The autonomous vehicle (AV) is one of the emerging technologies of the new age that has the potential to restructure transportation infrastructure. AVs are able to sense their surroundings and move around with control and self-sufficiency. AVs can contribute towards reducing traffic congestion on the roads, improving the quality of life, and achieving the highest levels of traffic safety. Thus, this type of vehicle can be integrated into the logistics industry. Due to the presence of several AVs, selecting a standard and efficient AV for logistics planning is a great challenge. The selection of an AV depends on many conflicting and essential criteria. Given its efficiency and reliability in dealing with conflicting criteria, a comprehensive multi-criteria decision-making (MCDM) approach was applied to solve the problem of selecting the optimal AV. However, the MCDM selection process is based on human judgment, which can be ambiguous. Accordingly, uncertainty was handled using type-2 neutrosophic numbers (T2NN). Initially, the method based on the removal effects of criteria (MEREC) was extended under T2NN and employed to assess and prioritize criteria. Then, the combined compromise solution (CoCoSo) method was extended under T2NN and applied to rank the candidate substitutions. To confirm the feasibility of the applied approach, an illustrative case study of four AVs was introduced. A sensitivity analysis was performed by changing the weights of the criteria and some other parameters to confirm the validity and stability of the proposed approach. In addition, a comparison analysis with other MCDM approaches was conducted to show the effectiveness and reliability of the applied approach. This research provides useful information for policymakers in the field of logistics. Finally, the results indicate that the velocity of AVs criterion is the most influential criterion in the selection of an intelligent AV.

A hybrid approach based on fuzzy BWM and MAIRCA for selection of engine in rotary wing unmanned aerial vehicle design

The use of Unmanned Aerial Vehicle (UAV) platforms has been increasing day by day and it has become an important technology. In this study, how the engines should be selected in the design of a rotary wing UAV system is considered a multi-criteria decision-making (MCDM) problem. This MCDM problem has not yet been encountered in the literature. Therefore, a hybrid MCDM approach based on the fuzzy Best Worst Method (BWM) and Multi Attributive Ideal-Real Comparative Analysis (MAIRCA) is proposed to solve this problem. In the proposed approach, the decision makers determine 6 criteria (KV value, thrust, weight, efficiency, battery, electronic speed controller (ESC)) and 6 different engine (A1, A2, A3, A4, A5, A6) alternatives. The fuzzy BWM was used to calculate the weights of criteria, while the MAIRCA was used for the selection of alternatives. According to the results obtained, the three most effective criteria were thrust, KV value, and weight, respectively. The three best engine options were found as A3, A1, and A6. Moreover, sensitivity analysis was performed to observe the change in the ranking of alternatives according to different weights of criteria. MABAC, MARCOS, and COPRAS methods were used to compare the alternative rankings found with the MAIRCA.

A GIS-based multi-criteria decision-making approach for site suitability analysis of solar-powered hydrogen production in the Souss-Massa Region, Morocco

The transition towards sustainable energy systems underscores the significance of hydrogen production through renewable resources. This study investigates the potential for solar-hydrogen conversion in the Souss-Massa region using a comprehensive approach that integrates the Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) tools. Ten distinct criteria, grouped into technical and economic categories, are evaluated to identify optimal areas for hydrogen generation, with environmental criteria being used as exclusion factors. Hydrogen production potential emerges as the primary determinant, with the western region, emerging as a focal point for solar-hydrogen projects. A comparative analysis between AHP and Fuzzy AHP (FAHP) results demonstrates the robustness of the methodology. Sensitivity analysis sheds light on the impact of criteria weighting on suitability outcomes, providing valuable insights for decision-makers and energy stakeholders. The study further quantifies avoided CO2 emissions and presents compelling Key Performance Indicators (KPIs) such as the Levelized Cost of Hydrogen (LCOH) and the Levelized Cost of Electricity (LCOE). The LCOE is found to be as low as 35.75 $/MWh, positioning the proposed solar-hydrogen conversion selected location as a cost-effective energy site. The LCOH for the designated location stands at 2.9 $/kg, reflecting its competitive stance. These findings collectively underscore the environmental and economic viability of sustainable hydrogen production in the Souss-Massa region.

A sustainable green reverse logistics plan for plastic solid waste management using TOPSIS method.

Recycling solid plastic waste is helpful for resource utilisation in a sustainable manner, and this can lead to reverse logistics to recover waste in supply chain management. In developing economies, it is very essential to recover waste and recycle it, as mismanagement of it could hasten the development of negative socioeconomic and environmental issues. This paper investigates plastic waste recycling by means of reverse logistics management. We feature Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which is a multi-criteria decision-making approach to selecting a suitable warehouse that will assist the decision-maker and supply the product to the re-manufacturing cell by inspecting the waste. The paper also focuses on the carbon emissions that are emitted during re-manufacturing through a mathematical model that minimises the total cost and total carbon emissions. A case study of the plastic re-manufacturing industry in Tripura, India, is shown here to present the steps of the decision support system. The model is programmed with real-life data from the case study and yields a total cost of Rs. 2894.37 and total emissions of 414.15 gm/lt, when the disposal cost is considered; without it, the total cost is Rs. 2668.69 and the total emissions are 413.54 gm/lt. The results obtained are promising for reducing carbon emissions from the recycling process of plastic waste at a lower cost. This research will also help the environment cope with plastic waste, which has become a threat to nature, as well as carbon emissions that come from the industry. Finally, some managerial insights and suitable analyses with pictorial representation are proposed.

An integrated decision support framework for resilient vaccine supply chain network design

Designing resilient supply chain networks for vaccine development and distribution requires reliable and robust infrastructure. This stud develops a novel two-stage decision support framework for configuring multi-echelon Supply Chain Networks (SCNs), resilient supplier selection, and order allocation under uncertainty. Resilient supplier selection is done using a hybrid Multi-Criteria Decision-Making (MCDM) approach based on Best-Worst Method (BWM), Weighted Aggregated Sum Product Assessment (WASPAS), and Type-2 Neutrosophic Fuzzy Numbers (T2NN). A robust multi-objective optimization model is then built for order allocation considering resiliency scores, reliability of facilities, and uncertain supply and demand. The objectives are to minimize the total cost of SCN design, maximize the resiliency score, and maximize the reliability of SC, respectively. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) is developed to tackle the problem on large scales, tuned by the Taguchi design technique. The NSGA-II solution is compared to the ε-constraint and Multi-objective Particle Swarm Optimization (MOPSO) solutions using test problems. We demonstrate the superiority of the suggested NSGA-II method over the two competing methods according to five performance metrics. A case study is then investigated to illustrate the applicability and effectiveness of the offered methodology for COVID-19 vaccine distribution in a developing country. It is revealed that the models and algorithms can treat the problem optimally, such that Germany is the main source (approximately 25.61%) while India does not contribute to the supply of vaccines.

Archimedean [formula omitted]-norm and [formula omitted]-conorm based intuitionistic fuzzy WASPAS method to evaluate health-care waste disposal alternatives with unknown weight information

Health-care waste (HCW) contains numerous hazardous, infectious, and radioactive contents that may cause serious health issues for society and drastic environmental problems. Therefore, it is crucial to dispose of HCW safely and appropriately. Four commonly used HCW disposal methods are incineration, steam sterilization, microwave, and landfill disposal. To select an appropriate HCW disposal method, there are several conflicting criteria. Furthermore, when information is lacking due to uncertainty and criteria weighing conditions are also unknown, the decision to choose an appropriate HCW disposal method becomes more challenging. So, the objective of this paper is to introduce a novel integrated multi-criteria group decision-making (MCGDM) approach to evaluate HCW disposal methods in which incomplete information is quantified using intuitionistic fuzzy sets (IFSs), unknown criteria weights are evaluated using the maximizing deviation method, and the evaluation of HCW disposal methods is done by applying the Archimedean t-norm and t-conorm-based interactive intuitionistic fuzzy weighted aggregated sum product assessment (WASPAS) method. Herein, the Archimedean t-norm and t-conorm cover a wide range of t-norms and t-conorms, including the Algebraic, Einstein, Hamacher, and Frank, etc., by adopting prescribed combinations of additive generators. The proposed MCGDM approach has been applied to evaluate the above-listed four HCW disposal methods for a case study conducted by Mishra et al. (2020) in the context of India. A sensitivity analysis is performed to examine the impact of changes in the parameters involved in the proposed MCGDM approach. A comparative study is also performed with some well-known multi-criteria decision making(MCDM) and MCGDM methods to demonstrate the consistency and stability of the proposed approach. Findings suggest that the newly developed MCGDM approach is more general, flexible, and provides realistic results to evaluate HCW disposal methods under uncertainty and unknown criteria weight information.

Identifying And Ranking the Factors Affecting the Cultural Excellence of The Higher Education Institutions, Using the Multi-Criteria Decision-Making Approach (AHP-TOPSIS)

The purpose of this study is to identify and rank the factors affecting the cultural excellence of university, using multi-criteria decision-making techniques in Guilan Province. The study is an applied that has an exploratory and descriptive nature. The statistical population includes 3663 experts, professors, and managers of the Islamic Azad University branches, Payam Noor University, and Guilan University. According to Morgan table, 331 people were selected as the sample size and the initial questionnaire was stratified-randomly distributed. Also, the opinions of 15 experts were used to evaluate the factors in the TOPSIS and AHP models. The instrument for data collection is researcher-made and standard questionnaires, whose validity and reliability have been confirmed through content validity, construct validity and Cronbach's reliability coefficient, respectively. In this regard, descriptive analysis, structural equations and AHP-TOPSIS multi-criteria decision-making techniques were used to rank the research variables. The results obtained from the opinions of experts and stakeholders of universities using multi-criteria decision-making methods showed that "quality" with a weight ratio of 0.274 has the highest priority. Also, "Professional competence culture of professors" with a weight ratio of 0.185, "Imitation of the myths of universities" with a weight ratio of 0.116 , "Management model" with a weight ratio of 0.106 , "Learning" with a weight ratio 0.099, "regional participation" with a weight ratio of 0.060, "university communication culture with stakeholders" with a weight ratio of 0.043, "empowerment" with a weight ratio of 0.038 , "intellectual capital culture" with the weight ratio of 0.030 , "research" with the weight ratio of 0.026, and finally the factor of "disciplinary culture" with the weight ratio of 0.025 are in the second, the third, the fourth, the fifth, the sixth, the seventh, the eighth, the ninth, the tenth and the last priority, respectively.

Decision-making approaches for optimal seismic/energy integrated retrofitting of existing buildings

Given the ambitious targets of carbon emission reduction set for the very near future, it is now expected that retrofitting operations on existing buildings aim both at reducing their operational energy consumption and at improving their seismic performance. Indeed, it is now well acknowledged that, if a sole energy efficiency upgrade is provided to a given building, in case of an earthquake occurrence, double economic and environmental losses will be experienced due to both the lost investment for energy retrofitting and the repair and retrofitting activities for post-earthquake damage. Moreover, social losses may also be experienced in terms of casualties, injured or homeless due to the seismic and structural deficiencies of the existing structure. To aid thus the process of a coupled seismic/energy renovation of the existing building stock, several multi-criteria decision-making (MCDM) approaches have been developed for the identification of optimal retrofitting solutions for buildings. Such procedures typically consider a range of economic, social, technical, and, more recently, environmental aspects that are assumed to be of interest to decision makers (e.g., installation cost, duration of works, architectural impact, need for specialised workers, etc.). The present study demonstrates the application to a case-study school building of two different MCDM approaches, which account for seismic vulnerability and energy efficiency, as well as related environmental impacts of buildings. The main differences between the two procedures are explored in terms of considered decision-making parameters and corresponding weights, rankings of retrofitting options and identification of the optimal retrofitting strategies.

How should you heat your home in the green energy transition? A scenario-based multi-criteria decision-making approach

The choice of heating system is significant for city planners and building owners alike, and many important areas, such as the well-being of residents, climate change impact and resource efficiency, may influence the choice. Understanding how to balance these areas is crucial for effective decision-making that can contribute to sustainable development and the green energy transition. However, these decisions represent complex problems where disparate knowledge areas must be considered simultaneously. When faced with this type of decision-making problem, employing different multi-criteria decision-making methods is common. However, such methods only provide a snapshot of which alternative is preferred and because of this, their results may become obsolete due to changes in the performance of alternatives or the value perceptions of the decision-makers. To overcome this challenge and to improve the longevity and reliability of multi-criteria decision-making results, the authors of this study explored a novel approach to producing semi-dynamic results through scenarios, which were used to consider possible future changes to the alternatives' performance and the decision-makers’ value perceptions. The application of scenarios in the multi-criteria decision-making method enabled nuanced information to be produced on how the performance of different heating alternatives may change under different plausible futures. This approach was demonstrated by applying it to the case of residential heating in Denmark, where results showed that while final rankings varied across both scenarios and ranking methods, solar heating was the preferred alternative, while the oil boiler alternative performed the worst. Overall, this study highlights the importance of considering likely future changes to both the performance of alternatives and the value perceptions of decision-makers when making decisions with long lifetimes and suggests an approach for doing this.

Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach

The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment. The study aims to select the best vendor for supplying medical equipment based on Emergency Care Research Institute (ECRI) standards. The multi-criteria decision-making approach has been adopted through three methods; Multi-Objective Optimization by Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The criteria of selection are divided into general, technical, and financial. The criteria are weighted using three methods: CRITIC, entropy, and expert judgment. The Vendor Evaluation Program for Medical Equipment (VEPME) is designed to automatically select the best vendor. Medical imaging equipment is selected to test the program by four modalities: X-ray equipment, CT, MRI, and ultrasound. The best scenario was given by the entropy-TOPSIS. As a result, this methodology was adopted by the program. The results demonstrate the robustness of the proposed methodology by comparing the VEPME output to expert judgment.

Development, characterization and application of starch-based film containing polyphenols of piper betle L. waste in chicken meat storage

The current study aimed to develop a sustainable solution to extend the shelf life of chicken meat by developing starch-based functional film embedded with polyphenolic extract of waste petioles of betel leaf (BLP). The results showed that loading of the extract significantly (p < 0.05) improved flexibility, thickness, water solubility, DPPH radical scavenging activity, and UV light protection ability by enhancing intermolecular interactions among potato starch, guar gum, and the extract. The developed film showed optimum mechanical and water barrier properties at a 4% BLP extract concentration computed through TOPSIS method (A multi-criteria decision-making approach). During the shelf life study, the extract embedded film maintained the quality of chicken meat for up to 12 days at refrigerated temperature. Biodegradation time of the extract-blended films was considerably decreased to 14 days from 28 days for the native film, indicating suitable alternative to non-biodegradable film for storing the raw meat.

Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS

This work addresses the issue of multi-label feature selection by extending the CODAS technique with a q-rung orthopair hesitant fuzzy multi-criteria decision-making approach. The methodology of proposing CODAS methodology in the q-rung orthopair hesitant fuzzy set environment and utilizing it in a multi-label feature selection problem is the first and only such extension of the CODAS algorithm in the literature. To generate a decision matrix, the proposed method MFS q-ROHFS MCDM views the technique as an information fusion process. Experimental results are compared to other ways using the same performance criteria to exhibit the efficacy and superiority of the suggested approach.