Compromise Ranking Method Research Articles

Multi-attribute optimization of drilling CFRP/Ti-6Al-4V alloy hybrid stacks using VIKOR

Drilling carbon reinforced polymer composites (carbon fiber-reinforced polymers, CFRP) and the hole quality produced are highly critical and significantly influence the performance and reliability of structures used in aircraft components. When CFRP composites are stacked together with titanium alloy, the damage caused by the machining operation is incalculable due to the burr and chip evacuation of metallic phases. In this article, efforts were made toward the identification of optimal machining conditions in drilling CFRP/titanium hybrid stacks. Experimental investigations on dry drilling of CFRP/titanium stacks were conducted with the aid of tungsten carbide drills. This research article discusses an improved compromise ranking method named VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) to determine the optimal machining parameters in drilling of CFRP/titanium stacks to produce high-quality holes. Attributes measured from experimental trials are: delamination factor of CFRP, burr height of titanium alloy, thrust force, torque, surface roughness, roundness and hole diameter of CFRP and titanium alloy. Experimental trial 13 with a combination of speed of 30 m/min, feed of 0.025 mm/rev was chosen as an ideal machining parameter in drilling CFRP/Ti-6Al-4V stacks without any trade-off. Confirmation tests convey that the results agree well with optimal parameters and the decision making in drilling such multimaterial stacks is highly consistent and judicious. In regard to the optimal parameters determined, investigations on tool life were performed and a tool life of 20 min for 0.10 mm flank wear land was observed.

An MCDM optimization based dynamic workflow scheduling used to handle priority tasks for fault tolerance in IIOT

Cloud computing's prominence can be mainly attributed to its convenient on-demand service delivery via the internet. The difficulty in managing these requests and allocating them optimally is exacerbated by the growing number of users making them and the variety of criteria used to apply cloud resources. Some of these difficulties include scheduling work while considering the user's Quality of Service (QoS) preferences, ensuring adequate load balancing, and adapting to the ever-changing conditions of the cloud environment. As server capabilities evolve, static load balancers, which distribute requests using fixed ratios of available resources, fail to provide optimum throughput. It has been shown that no other scheduling algorithms offer an adaptive method that considers both load balancing and maximizing the QoS criteria. The authors of this study present a novel adaptive strategy for dealing with this issue by fusing the best-worst multi-criteria decision-making method (BWM) with the compromise ranking method (VIKOR). Task priorities are determined by using the VIKOR method as a decision-maker. Numerical experiments are used to verify the validity of the suggested method, and the methodology is compared to other scheduling methods in terms of a variety of performance criteria. The simulation findings show that the presented method outperforms its rivals regarding throughput, makespan, waiting time, virtual machine (VM) utilization, and VM usage cost across the board of simulated experimental settings.

The use of VIKOR Method in Finding the Optimal Solution for a Special-Purpose Geodetic Network Design

This study deals with the use of VIKOR method in finding the optimal solution for a special-purpose geodetic network design. It is about a multi-criteria compromise ranking method developed in 1986. Based on previously defined criteria functions related to precision and reliability, four acceptable alternative solutions were firstly established. Then, with the aim of finding the optimal one, those solutions were subjected to VIKOR method. The geodetic micro-network used in this study was simulated as a trilateration one and consisted of six control points discretizing a structural geometry as well as four, five or six reference points (pillars), depending on what alternative solution it was about. The optimal network design should have ensured the detection of deviations of the control points' positions in accordance with a priori introduced tolerances and constraints. It turned out the approach based on VIKOR method is a very efficient tool in tasks involving multiple conflicting requirements referred to a geodetic engineer and in the cases when the decision must be made in a short term.

Application of multi-attribute decision-making methods for the selection of conveyor

In the present time of innovation, conveyor is an exceptionally indispensable part and has huge significance for material handling in various process and manufacturing industries. It is made with precisions, and the expenses are relatively high and should work with better productivity. The selection of the best conveyor is a crucial task, and the designers need to recognize different attributes that will influence the functionalities of the conveyor system to limit bottlenecks in the system. Researchers have worked on strategies for finding the best optimum solution for various selection problems, but conveyor selection using selected methods is not reported. Therefore, the present work aims to the selection process of the best option for conveyor by using four selected decision-making methods such as analytical hierarchy process, technique of order preference by similarity to ideal solution, compromise ranking method and Deng’s similarity-based method. The selection is done among four alternatives based on six attributes, viz. fixed cost each hour, variable cost each hour, conveyor speed, product width, product weight and flexibility. The analytical hierarchy process is used to determine weights of the attributes based on relative importance of each attribute. It is observed that A3 conveyor is best suitable conveyor. Hence, the proposed strategies help manufacturers to examine and choose the best conveyor.

Selection of blends of ethanol with petrol for SI engine using TOPSIS and VIKOR methods

India and other agricultural countries grow large quantities of sugar cane and ethanol is a by-product of the sugarcane industry. The blending of ethanol with petrol can save tremendous amount of petrol. In the present study, experiment was carried on the SI engine by means of various blends of ethanol with petrol such as E5, E8, E10 and E12, and the various engine performance variables were recorded such as brake thermal efficiency, volumetric efficiency, air-to-fuel ratio and exhaust heat. The two selected multi attribute decision making methods viz: technique for order preference by similar to ideal solution and compromise ranking method have been utilized in determining the rank of blends. It has been seen from the ranks obtained using both the methods that the blend E10 is the best alternative with petrol, E5 is the second best where as E8 and E12 are third and fourth best alternative respectively.

Methodology for integrated multicriteria decision-making with uncertainty: Extending the compromise ranking method for uncertain evaluation of alternatives

Making a decision usually means selecting one from different alternatives to solve a problem according to a set of criteria. Multicriteria analysis usually offers a quantitative approach to ease decision-making by ranking the alternatives. However, uncertainty can arise when rating the importance of criteria and the adequacy of each alternative for each criterion, due to two factors: first, answers are usually expressed in linguistic terms that do not have a unique quantification; and second, there might be a lack of confidence in the response. Most multicriteria procedures combine fuzzy numbers and linguistic scales to deal with the first factor, but underestimate confidence issues. In this context, this work develops a Methodology for Integrated Multicriteria Decision-making with Uncertainty (MIMDU), which considers both factors of uncertainty. MIMDU is structured in three phases: (1) a novel procedure based on fuzzy rating scales to model uncertain opinions; (2) a fuzzy formulation of the compromised ranking method to rank the alternatives; and (3) a systematic procedure for results' interpretation comparing a crisp ranking (without uncertainty) and a fuzzy-based ranking (with uncertainty). The methodology is illustrated with a generic example case, aiming to prove its potential application in any sector. Results show that MIMDU helps decision-makers to choose the most reliable alternative, since significant differences in ranking with and without uncertainty can be addressed. A sensitivity analysis is carried out to bare the effect of confidence in the alternatives evaluation, concluding that worse rankings are obtained for alternatives that are less confidently evaluated. A final comparison with the standard fuzzy VIKOR method shows MIMDU's major preciseness in modelling non-confident opinions and providing more useful and complimentary information to better assist decision-making.

Combining decision making algorithms to improve accuracy of the course assessment rank

Assessment activity is important to keep the quality of student’s knowledge. This study aims to combine decision making algorithms to improve accuracy of the course assessment activities rank to evaluate the student’s knowledge automatically. This study use Analytical Hierarchy Process (AHP) and VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) as decision making algorithms. AHP and VIKOR are Multi-Criteria Decision Making (MCDM), where VIKOR is compromise ranking method that is expected to improve the accuracy of the ranking results. AHP and VIKOR algorithm which are combined in this study are named AVI. The experiment result with 6 types of assessment as criteria shows that AVI capable to increase the accuracy value of assessment ranking result until 1.75 times more accurate/higher percentage than using AHP or VIKOR only. This result has implications for the similar research of decision support systems, for different case studies, it can be applied the AVI combination method to improve the accuracy of ranking results.

Transition management theory-based policy framework for analyzing environmentally responsible freight transport practices

The freight transport industry of developing nations are trying very hard to achieve environmental sustainability in their logistics business. Meanwhile, it is essential to identify the transformation path towards sustainable freight transport for every nation. This paper has presented a framework based on transition management (TM) theory to identify, classify, and measure the important environmentally responsible transport practices (ERTPs). This work utilizes a two-step methodology comprised of a grey clustering (GC) algorithm and a compromise ranking method, i.e., VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for prioritization of ERTPs performance. The GC algorithm is used to classify the ERTPs based on their impact on selected transport processes. Initially, this study identifies thirty-five ERTPs and four transport performance clusters. The proposed framework is validated with the Indian freight transport industry. The GC algorithm classifies twenty-one and fourteen practices as a high priority and moderate priority, respectively. The VIKOR method is used to compute the group utility, individual regret, and possibility value of high priority ERTPs. The ERTPs such as developing efficient freight terminal, compliance with government transport emission law and practice, promoting the use of the green container, environmental certification of freight carriers, and using alternative fuels are found as poor performing practices in the Indian freight transport industry. The proposed decision model robustness is tested with the sensitivity analysis, and a final ranking of the high priority ERTPs is presented. The outcomes of this research help logistics practitioners and policymakers in managing the ERTPs of freight logistics systems and develop a roadmap for improving freight transport sustainability.

Fuzzy Multi Criterion Decision Making Method to Analyze Performance of Banking Sector

Performance evaluation of any financial institution is extremely important to look after the health and prospect of the institution. In many research of performance evaluation analysis of banks, several ratio parameters are used mostly in statistical analysis. Designing effective and comprehensive model for evaluation process of financial matters in banking sector is complex due to multiple criteria and parameters, mostly uncertain in nature. This paper presents a comprehensive process considering several financial criteria of several alternatives on the basis of several expert’s (decision maker’s) opinion and subjective judgment. Intensity of importance is represented in fuzzy scale. We used fuzzy AHP-preference programming (FPP) to obtain priority weights associated with each criteria and compromise ranking method (VIKOR) considering Market Capital, Net Sales, Net Profit, Total Assets, and Other Income in ranking alternatives. A case study involving ten active Indian Public Sector Unit (PSU) banking industries is undertaken to illustrative the feasibility of the suggested approach. A sensitivity analysis is also carried out for checking the method reliability.

Material selection for rotational molding process utilizing distinguished multi criteria decision making techniques

Abstract Rotational Molding is defined as an emerging plastic processing technique wherein a privilege of stress free plastic products is achievable. Linear Low Density Polyethylene (LLDPE) has always been on highest priority as base resin for roto moulded product. However, LLDPE lacks in the criteria where strength is a priority in few applications. Additives can build gap to enhance the mechanical properties. A proper selection of additive to deliver an appropriate needed mechanical property in roto moulded product has always been challenging. Multi-criteria decision-making (MCDM) techniques were used to address the challenge of choosing additive with different properties from a large number of alternatives. In the present research, decision models like MOORA (ranking method based on ration analysis) and TOPSIS (a compromise ranking method) techniques were made as a source of aid to evince the fibre that can be opted in mixing with the base resin for roto moulded product. A comparative study is evaluated in this research considering these two methods with distinguished natural fibres using various attribute. It has been verified in the past that MCDM methods can be used to solve the problems of selecting material in real time. The results thus obtained are relatively satisfactory and can be used to be blended with the resin in design stage of roto moulded product. Coir in the category of natural fibres has been concluded as the material on highest ranking based on the attributes utilized in solving the techniques.

Optimization of Process Parameters in Abrasive Water Jet Machining of Inconel 718 Using VIKOR Method

In this work, an attempt was made to identify the optimized parameter combination in abrasive jet machining of Inconel 718 alloy. Experiments were conducted based on L9 Taguchi array. Pressure, standoff distance and abrasive flow rate were considered as input parameters. M18 standard washer of 20 mm inner diameter and 34 mm outer diameter was made on a sheet of thickness 2 mm. The qualities of the washer were measured with respect to roundness, taper angle, material removal rate and surface roughness. Improved compromise ranking method also known as VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) method was used in this work to identify the optimized parameter combinations. Experiment number 7 with 180 MPa pressure, 0.42 kg/min abrasive flow rate and 2 mm standoff distance was identified as the best parameter combination.

An adaptive scheduling approach based on integrated best-worst and VIKOR for cloud computing

Cloud computing is a new distributed environment to provide on-demand services through the internet and has become popular due to this specific feature. By increasing the count of user requests and different criteria in applying the cloud resources, there exist challenges for managing these requests and their optimal allocation. Some of these challenges consist of considering the dynamic nature of the cloud environment, finding the values of the different criteria and the scheduling tasks by considering the user’s Quality of Service (QoS) preferences, load balancing, etc. Static load balancers distribute requests based on pre-known server capability ratios and these models do not produce optimal throughput when the server capabilities change overtime. None of the other scheduling algorithms is able to provide an adaptive approach to consider both of the load balancing and optimizing the QoS requirements. To solve this problem, this paper proposes a new adaptive approach based on a combination of the concept of the best-worst multi criteria decision-making method (BWM), and compromise ranking method (VIKOR). The VIKOR method is implemented as a decision maker to specify the task priorities. The proposed approach is validated with numerical experiments and is compared with the existing scheduling algorithms over different performance metrics. The simulation results indicate that the proposed approach improves the performance metrics like throughput, makespan, waiting time, virtual machine (VM) utilization and VM usage cost for all considered experimental scenarios in comparison with its counterparts.

Comparative Analysis of Multi-Criteria Methods for the Enhancement of Historical Buildings

The protection of cultural heritage is essential to preserve the memory of the territory and its communities, but its enhancement is also important. In this perspective, the theme of choosing the best use for historic buildings, which often make up a substantial and widespread part of real estate and which can become a driving force for the sustainable development of cities, is important. These decision-making processes find effective support tools in Multi-Criteria Decision Making (MCDM) methods, able to consider the multiple financial, social, cultural, and environmental effects that the enhancement project generates. In order to identify the most appropriate evaluation approach to select the best use of the building, this paper proposes a comparison between some of the best-known MCDM methods: Analitic Hierarchy Process (AHP), ELimination Et Choix Traduisant la REalité (ELECTRE), Tecnique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the Compromise Ranking Method (VIKOR). The comparative analysis gives rise to the validity of the AHP, which is useful for reducing the problem into its essential components, so as to make a rational comparison among the design alternatives based on different criteria. The novelty of the research is the characterization of the hierarchical structure of the model, as well as the selection of criteria and indicators of economic evaluation. The application of the model to a real case of recovery and enhancement of a former convent in the province of Salerno (Italy) verifies the effectiveness of the tool and its adaptability to the specificities of the case study.

Selection of energy matrix sources in Chile using a fuzzy logic decision approach

Chile’s 2050 energy policy ultimate goals are to produce a sustainable model of economic growth respectful of the environment where energy is produced efficiently and reliably. Renewable energy sources are considered the main drive for developing by 2050 at least 70% of the total energy in Chile. This study aims to provide a quantitative analysis for the selection of the most sustainable energy production methods using the compromise ranking method (VIKOR) that uses maximum group utility for the majority and a minimum of individual regret for the opponent. Since all evaluations are provided via intervals, the possible degree theory is used to compare them. Nine major criteria are critically used for this purpose and prioritized using analytical hierarchical process (AHP). Since Chile’s energy production matrix still relies heavily on fossil fuels with major concerns of GHG emissions, all major potential energy sources in Chile are considered including ocean energy in addition to nuclear energy. This study shows that biomasses are the best compromise solution and that traditional and modern nuclear energy plants score consistently better than solar power. Large hydro power plants rank very high but in light of the social opposition present in the country, they might not be easy to build as hoped. Ocean power is far superior to geothermal energy and comparable to wind power and for this reason it should be considered together with nuclear power for the future Chilean energy matrix.

Multi-criteria decision-making approach to material selection in tribological application

This paper presents application of various multi-criteria decision-making (MCDM) techniques to material selection in tribological application. The alternative materials considered for ranking are variants of AISI 4140 which is nitrided and then coated with various low-friction surface coating materials. This study analyses and discusses the priority settings on the basis of constructed model which compares the ranking outcomes among simple additive weighting (SAW), multiplicative analytic hierarchy process (MAHP), technique for order preference by similarity to ideal solution (TOPSIS), modified-TOPSIS (M-TOPSIS) and compromise ranking method (VIKOR). Attribute weights obtained by analytic hierarchy process (AHP), are used as the inputs and outputs are materials' rankings on the basis of material selection index (MSI), which help designers and engineers to reach a consensus on materials selection for a specific application. The ranks obtained by various methods are compared. Results indicate that suggested method can effectively be applied to similar problems.

Multi-criteria decision-making approach to material selection in tribological application

This paper presents application of various multi-criteria decision-making (MCDM) techniques to material selection in tribological application. The alternative materials considered for ranking are variants of AISI 4140 which is nitrided and then coated with various low-friction surface coating materials. This study analyses and discusses the priority settings on the basis of constructed model which compares the ranking outcomes among simple additive weighting (SAW), multiplicative analytic hierarchy process (MAHP), technique for order preference by similarity to ideal solution (TOPSIS), modified-TOPSIS (M-TOPSIS) and compromise ranking method (VIKOR). Attribute weights obtained by analytic hierarchy process (AHP), are used as the inputs and outputs are materials' rankings on the basis of material selection index (MSI), which help designers and engineers to reach a consensus on materials selection for a specific application. The ranks obtained by various methods are compared. Results indicate that suggested method can effectively be applied to similar problems.

Application of AHP-VIKOR and GMDH framework to develop an indicator to identify utilisation potential of wave energy converter with respect to location

The potential of analytical hierarchy process (AHP)-rough number based compromise ranking method (also known as VIKOR) multi-criteria decision-making (MCDM) and group method of data handling (GMDH) multimodal predictive method was analysed for smart representation of 'utilisation potential' of wave energy converters from specific locations. The significant parameters were identified by considering different case studies and their influence on converter efficiency. The soft-computation methods like AHP-VIKOR and GMDH were used for the first time to find the relative priority values of the parameters. The results from the multi-method estimation model were validated with the help of multi linear regression equation and certain real-time case analysis. With an accuracy of above, 99% the ensemble MCDM-ANN model depicted reliability, which ensures the author of its wide application for real benefits like cost reduction and efficiency maximisation of converters in the utilisation of the potential wave energy of locations.

Supply Chain Partner Selection under Cloud Computing Environment: An Improved Approach Based on BWM and VIKOR

The wide application of cloud computing technology makes supply chain partner share information effectively and increase corporate profits. However, in cloud computing environment, the evaluation process of supply chain partner selection is dynamic and fuzzy, and its evaluation index is uncertain. To solve these problems, this paper proposes a new method combed with rough number, best-worst multicriteria decision-making method (BWM), and compromise ranking method (VIKOR). Firstly, Rough number is used to integrate data from different evaluation matrix. Secondly, rough number improves a new method, BWM, to get RBWM criteria weight methods. Thirdly, the rough numbers are introduced into VIKOR and combined with RBWM to evaluate and sort the supply chain partners. Finally, an example is given to demonstrate the rationality and feasibility of the method.

Multi attribute outranking approach for supplier selection

Multi attribute outranking approach has been widely used in supply chain management. Compromise ranking and Outranking method has been used extensively for solving the multi criteria decision problems. Elimination and Choice Translating Reality (Electre) and Preference Ranking Organization Method for Enrichment Evaluations (Promethe) are the most widely used outranking methods to solve multi-criteria decision problems. The above methods may be used to solve problems involving both conflicting qualitative and quantitative criteria. This work focuses on the application of improved outranking based method electre, for solving a real problem of supplier selection. A case study is done for selection of supplier for the spherical roller bearing for finding the rank of the alternatives. The need of this case study is to select the best possible supplier out of the available alternative suppliers.

A VIKOR-based approach for the ranking of mathematical instructional videos

PurposeIn the last years, the use of free-online instructional videos has gained popularity among educators and students. Its success is mainly based on the provision of fast and inexpensive access to educational contents which can be consulted at the own convenience of students, all over the world. Free-online platforms as YouTube offer access to more than ten million instructional videos. The purpose of this paper is to assess and rank the educational quality of free-online instructional videos from a multidimensional perspective.Design/methodology/approachIn this paper, the authors propose a MCDM approach based on a compromise ranking method, VIKOR. The approach integrates a normalization process which is especially suitable for situations where the nature of the different decision-making criteria is such that it does not allow homogeneous aggregation.FindingsWith the proposed normalization approach, the initial valuations of the alternatives with respect to the criteria are transformed in order to reflect their similarity with a given reference point (ideal solution). The normalized data are then integrated in a VIKOR-based framework in order to obtain those mathematical videos closer to the ideal video from the instructors’ perspective.Originality/valueThe ranking of instructional videos based on their quality from an educational multidimensional perspective is a good example of a real decision-making problem where the nature of the criteria, qualitative and quantitative, implies heterogeneous data. The proposed IS-VIKOR approach overcomes some of the problems inherent to this real decision-making problem.