Conflicting Evaluation Criteria Research Articles

Determining the appropriate natural fibers for intelligent green wearable devices made from biomaterials via multi-attribute decision making model

Intelligent and green wearable technology becomes essential for new modern societies. This work introduces a multi criteria decision making model to properly assess and compare relative desired criteria for selecting the most suitable constituents for green body wearable bio-products made from bio-based materials. It aims to enhance the sustainability of intelligent green wearable devices by providing support in the selection process of lightweight, eco-friendly materials suitable for personal body wearable bio-products made of natural fiber composites to improve qualities that may help in better monitoring human vital signs and thereby address the health care concern. The relative intrinsic characteristic and merits of various natural fibers were utilized to compare and evaluate their relative performance in bio-composites. The model considered several evaluation factors like mechanical performance including tensile strength and modulus of elasticity, comfortability including size and weight, availability, fiber orientation, cellulose content, and cost. Results have demonstrated different priorities of the considered natural fibers relative to each evaluation factor. However, the model was capable of properly evaluating and ranking the best fibers relative to the whole conflicting evaluation criteria simultaneously. The closeness of priorities in several cases emphasizes upon using such decision making models to be able to judge the relative merits of natural fibers for such applications. It can also help designers to avoid bias during determining the best alternatives considering several conflicting evaluation criteria.

Application of the R method in solving material handling equipment selection problems

In manufacturing industries, material handling equipment plays a vital role and is considered as one of the important pillars to increase production efficiency. Hence, the selection of appropriate material handling equipment for a specific task is well acknowledged, but the complexity of this selection process drastically increases with the rise in the number of alternative equipment available in the market and a set of conflicting evaluation criteria. To resolve this problem, several multi-criteria decision-making (MCDM) techniques have been proposed by past researchers. In this paper, the application potentiality of a newly developed MCDM technique, i.e. R method is explored while solving five material handling equipment selection problems, i.e. conveyor, automated guided vehicle (AGV), stacker, wheel loader and excavator. The derived ranking results are contrasted with other popular MCDM techniques to validate its potentiality in shortlisting the candidate alternatives from the best to the worst, which would ultimately help in improving the overall efficiency of the manufacturing processes.

Multi-objective optimisation methodology for stiffness combination design of bridge-embankment transition zones in high-speed railways

Bridge-embankment transition zones, in which unexpected amplifications of vehicle-track interactions and infrastructure degradation are concentrated, are critical areas of high-speed railways. To mitigate the dynamic issues induced by uncertain filler stiffness, an available stiffness combination of transition zone components is required. Combining with robust designs, a multi-objective optimisation methodology is proposed to determine the compromise design of transition zones, which considers trade-offs among dynamic stress, dynamic displacement and system robustness. An optimal stiffness combination of subgrade bed surface layer (E1) and graded broken stone area (E2) in a typical bridge-embankment transition zone is presented by employing this methodology. The results indicate that the Pareto fronts visually show the dynamic response contradiction. Based on the conflicting evaluation criteria, i.e., minimizing the displacement and stress of the subgrade and maximizing the system robustness, the knee points objectively render the best compromise design with E1 and E2 values of 1200 and 1000 MPa, respectively. Not only the dynamic response of the vehicle-track-subgrade system but also the negative effect brought by filler uncertainties are well controlled. Such a methodology is available for configuration design of projects in which uncertainties exist and design criteria are hard to weigh.

Multicriteria task classification in human-robot collaborative assembly through fuzzy inference

AbstractThe advent of new technologies and their implementation in manufacturing is accelerating the progress of Industry 4.0 (I4.0). Among the enabling technologies of I4.0, collaborative robots (cobots) push factory reconfiguration and prompt for worker empowerment by exploiting the respective assets of both humans and robots. Indeed, human has superior dexterity, flexibility, problem-solving ability. Robot excels in strength, endurance, accuracy and is expendable for risky activities. Therefore, task assignment problem in a production line with coexisting humans and robots cannot limit to the workload balancing among workers but should make the most of everyone respective abilities. The outcomes should not be only an increased productivity, but also improved production quality, human safety and well-being. Task assignment strategy should rely on a comprehensive assessment of the tasks from the viewpoint of suitability to humans or robots. As there are several conflicting evaluation criteria, often qualitative, the study defines the set of criteria, their metrics and proposes a method for task classification relying on Fuzzy Inference System to map each task onto a set of collaboration classes. The outcome of the study is the formal description of a set of evaluation criteria with their metrics. Another outcome is a Fuzzy Classification procedure that support production managers to properly consider all the criteria in the assignment of the tasks. The proposed methodology was tested on a case study derived from a manual manufacturing process to demonstrate its application during the process planning.

An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection

The number of green energy options in different fields is growing because of the need for reducing energy consumption and eliminating gas emission. One of these options is the use of eco-friendly cars produced by various manufacturers. Given the many available options and conflicting evaluation criteria, evaluation of such options becomes complex, and different multi-criteria decision-making (MCDM) approaches have been used to select the most suitable car in terms of eco-friendly car selection. Previous research has been somewhat limited with respect to consideration of interdependencies between evaluation criteria and multi-levels of preference. This paper proposes a new integrated MCDM approach with the capability for considering interdependent criteria for eco-friendly car evaluation and different levels of preference. An analytic network process (ANP) will be used to evaluate the levels of importance of interdependent criteria, and ELECTRE III will be modeled to include thresholds of preference. The introduced model, based on twenty-eight evaluation criteria, was demonstrated in a case study dealing with five alternative electric and hybrid cars. The results from this model were compared to a traditional decision-making method and better results were obtained from the model. The model can help users make proper decisions regarding their future car options in a comprehensive manner. Sensitivity analysis showed the robustness of the model under different setups.

Parallel multi-objective optimization approaches for protein encoding

One of the main challenges in synthetic biology lies in maximizing the expression levels of a protein by encoding it with multiple copies of the same gene. This task is often conducted under conflicting evaluation criteria, which motivates the formulation of protein encoding as a multi-objective optimization problem. Recent research reported significant results when adapting the artificial bee colony algorithm to address this problem. However, the length of proteins and the number of copies have a noticeable impact in the computational costs required to attain satisfying solutions. This work is aimed at proposing parallel bioinspired designs to tackle protein encoding in multiprocessor systems, considering different thread orchestration schemes to accelerate the optimization process while preserving the quality of results. Comparisons of solution quality with other approaches under three multi-objective quality metrics show that the proposed parallel method reaches significant quality in the encoded proteins. In addition, experimentation on six real-world proteins gives account of the benefits of applying asynchronous shared-memory schemes, attaining efficiencies of 92.11% in the most difficult stages of the algorithm and mean speedups of 33.28x on a 64-core server-grade system.

A review of 20-year applications of multi-attribute decision-making in environmental and water resources planning and management

Multi-attribute decision-making (MADM) is an umbrella term to describe a series of mathematical frameworks that, in essence, enable the decision-makers to evaluate the desirability of any feasible solution by considering a set of, often, conflicting evaluation criteria. Given their vast capabilities, the MADM methods are especially helpful for water resources planning and management. This review attempts to shed light on the roles of the MADM methods in the field of water resources decision-making during the last two decades. More than 320 scholarly published articles from 57 different countries were analyzed based on the geographic factors, the number of decision-makers involved, the type of MADM methods, the number of alternatives and criteria, the weight assignment methods, the viewpoints on uncertainty, and the subject of these studies. The results clearly revealed the ever-rising applications of the MADM methods for water resources management. It was also found that some regions, such as the Middle East, more frequently resort to these methods to address their water crisis problems. This review indicated that the analytical hierarchy process (AHP) was the most popular MADM method. Based on the reviewed studies and their results, three major recommendations can be made herein: (1) It is wise to address the uncertainty associated with the applications of the MADM methods in the field of water resources by conducting sensitivity analysis and/or resorting to probabilistic/fuzzy frameworks; (2) given the identified tendency toward subjective MADM, it is crucial to employ checking frameworks, such as the Delphi methods, to assess the consistency of the subjective evaluations; and (3) it is necessary to consider not only the technical criteria but the economic, environmental, legislative, and political evaluation criteria as well to account for the multidimensional nature of water resources problems.

Integrating interval-valued multi-granular 2-tuple linguistic BWM-CODAS approach with target-based attributes: Site selection for a construction project

The site selection procedure for mega-structure projects can be an effective tool that could considerably improve the amount of income generation potential. Evidently, selecting the optimal location to establish a shopping center in a metropolitan area of Tehran, Iran is challenging due to the complexity of several conflicting evaluation criteria as well as multiple alternatives. Moreover, the site selection process of a mega-structure project can be viewed as a multiple attribute decision making (MADM) problem. Additionally, in such complex environments decision-makers and policy-makers usually might utilize linguistic terms to evaluate different alternatives with respect to multiple evaluation criteria according to their experience, qualifications, and preferences. Moreover, in real-world decision-making assessment problems, decision-makers tend to assign specific target-values for the selection attributes to obtain their optimal choices. In response, this study solves a site selection problem using a hybrid multi-granular interval-valued 2-tuple linguistic variables and target-valued criteria with the Best-Worst Method (BWM) and COmbinative Distance-based ASsessment (CODAS). Using the suggested hybrid MADM approach can results in an optimal and comprehensive site selection process without information loss. Finally, the outcomes of the current study show that the proposed target-based method is an optimal technique for such decision-making problems.

A cyberGIS-enabled multi-criteria spatial decision support system: A case study on flood emergency management

ABSTRACTWith the increased frequency of natural hazards and disasters and consequent losses, it is imperative to develop efficient and timely strategies for emergency response and relief operations. In this paper, we propose a cyberGIS-enabled multi-criteria spatial decision support system for supporting rapid decision making during emergency management. It combines a high-performance computing environment (cyberGIS-Jupyter) and multi-criteria decision analysis models (Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution Model (TOPSIS)) with various types of social vulnerability indicators to solve decision problems that contain conflicting evaluation criteria in a flood emergency situation. Social media data (e.g. Twitter data) was used as an additional tool to support the decision-making process. Our case study involves two decision goals generated based on a past flood event in the city of Austin, Texas, U.S.A. As our result shows, WSM produces more diverse values and higher output category estimations than the TOPSIS model. Finally, the model was validated using an innovative questionnaire. This cyberGIS- enabled spatial decision support system allows collaborative problem solving and efficient knowledge transformation between decision makers, where different emergency responders can formulate their decision objectives, select relevant evaluation criteria, and perform interactive weighting and sensitivity analyses.

Green material selection for sustainability: A hybrid MCDM approach

Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection.

Autonomous Intersection Management systems: criteria, implementation and evaluation

The foreseeable large-scale deployment of autonomous vehicles in the near future raises the question of autonomous intersection management (AIM). Numerous AIM designs have been proposed, but they lack a common vision of what defines a good system. In this study, the authors discuss a set of conflicting evaluation criteria that need to be balanced in the design of an AIM system, but are often considered individually in the literature. They then introduce their own priority-based design, where an intersection controller assigns priorities to incoming vehicles. On being assigned a priority, vehicles then cross the intersection while maintaining a so-called brake-safe state with respect to higher priority vehicles, rendering the system robust. They have performed extensive simulations to showcase the properties of the proposed system, and notably that it satisfactorily balances their criteria while remaining efficient.

Software and Hardware FPGA-Based Digital Watermarking and Steganography Approaches: Toward New Methodology for Evaluation and Benchmarking Using Multi-Criteria Decision-Making Techniques

Evaluating and benchmarking software and hardware field programmable gate array (FPGA)-based digital watermarking are considered challenging tasks because of multiple and conflicting evaluation criteria. A few evaluation and benchmarking techniques/frameworks have been implemented to digital watermarking or steganography; however, these approaches still present certain limitations. In particular, fixing some attributes on account of other attributes and well-known benchmarking approaches are limited to robust watermarking techniques. Thus, this study aims toward a new methodology for evaluation and benchmarking using multi-criteria analysis for software and hardware “FPGA”-based digital watermarking or steganography. To achieve this objective, two iterations are conducted. The first iteration consists of two stages: discussing software and hardware “FPGA”-based digital watermarking or steganography to create a dataset with various samples for benchmarking and discussing the evaluation method and then discussing the test for software and hardware “FPGA”-based digital watermarking or steganography according to multi-criteria evaluation (i.e., complexity, payload and quality) to create a decision matrix. The second iteration applies different decision-making techniques (i.e., SAW, MEW, HAW, TOPSIS, WSM and WPM)) to benchmark the results of the first iteration (i.e., software or hardware FPGA-based digital watermarking or steganography approaches). Then, the discussed mean, standard deviation and paired sample [Formula: see text]-test results are used to measure the correlations among different techniques based on the ranking results. The discussion findings are described as follows: (1) the integration of developer and evaluator preferences into the evaluation and benchmarking for software and hardware FPGA-based digital watermarking or steganography, (2) the process of assigning weights and (3) visualizing large-scale data sample in either software or hardware FPGA-based digital watermarking or steganography algorithms.

Entropy-Based Weights for MultiCriteria Spatial Decision-Making

This paper presents an integration of entropy-based weights and a modified TOPSIS algorithm within a GIS-based multicriteria decision analysis (MCDA). Geospatial multicriteria decision-making (MCDM) problems typically involve a set of spatially feasible alternatives that are evaluated by multiple and conflicting evaluation criteria that vary in importance to the decision-maker(s). However, often in complex spatial decision-making problems the decision-maker(s) may be unable or unwilling to provide cohesive and exact numerical judgments regarding the relative importance or weights of criteria. An entropy-based object weighting scheme determines the weights for a set of criteria by quantifying the amount of information within the decision matrix and based on evaluation values. Information entropy is a measure of the degree of disorder within a system. It can quantify the amount of expected and useful information content within criterion values, and it measures the contrast intensity among a set of spatial criteria. This paper will present the implementation of entropy-based weights within a vector-based spatial problem for calculating the Heat Vulnerability Index within San Fernando Valley, Los Angeles.

Integrating the Ergonomics Techniques with Multi Criteria Decision Making as a New Approach for Risk Management: An Assessment of Repetitive Tasks -Entropy Case Study.

Nowadays, the health work decision makers need to analyze a huge amount of data and consider many conflicting evaluation criteria and sub-criteria. Therefore, an ergonomic evaluation in the work environment in order to the control occupational disorders is considered as the Multi Criteria Decision Making (MCDM) problem. In this study, the ergonomic risks factors, which may influence health, were evaluated in a manufacturing company in 2014. Then entropy method was applied to prioritize the different risk factors. This study was done with a descriptive-analytical approach and 13 tasks were included from total number of employees who were working in the seven halls of an ark opal manufacturing (240). Required information was gathered by the demographic questionnaire and Assessment of Repetitive Tasks (ART) method for repetitive task assessment. In addition, entropy was used to prioritize the risk factors based on the ergonomic control needs. The total exposure score based on the ART method calculated was equal to 30.07 ±12.43. Data analysis illustrated that 179 cases (74.6% of tasks) were in the high level of risk area and 13.8% were in the medium level of risk. ART- entropy results revealed that based on the weighted factors, higher value belongs to grip factor and the lowest value was related to neck and hand posture and duration. Based on the limited financial resources, it seems that MCDM in many challenging situations such as control procedures and priority approaches could be used successfully. Other MCDM methods for evaluating and prioritizing the ergonomic problems are recommended.

An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder

With increased worldwide awareness of environmental issues, healthcare waste (HCW) management has received much attention from both researchers and practitioners over the past decade. The task of selecting the optimum treatment technology for HCWs is a challenging decision making problem involving conflicting evaluation criteria and multiple stakeholders. In this paper, we develop an integrated decision making framework based on cloud model and MABAC method for evaluating and selecting the best HCW treatment technology from a multiple stakeholder perspective. The introduced framework deals with uncertain linguistic assessments of alternatives by using interval 2-tuple linguistic variables, determines decision makers’ relative weights based on the uncertainty and divergence degrees of every decision maker, and obtains the ranking of all HCW disposal alternatives with the aid of an extended MABAC method. Finally, an empirical example from Shanghai, China, is provided to illustrate the feasibility and effectiveness of the proposed approach. Results indicate that the methodology being proposed is more suitable and effective to handle the HCW treatment technology selection problem under vague and uncertain information environment.

Application of multi-criteria analysis in rural roads provision in developing countries

This study is based on an approach to resolve conflicts in decision making processes. It is necessary to recognize explicitly that most decision making processes involve multiple participants and are often characterized by multiple and conflicting evaluation criteria. In such situation, to be able to arrive at a decision, methods that contribute toward consensus building among the decision makers are required. The objective of this study is to devise a conflict resolution oriented decision making framework that can be used in decision making in the public arena. In this study a decision making framework was applied to a process of selecting a ward (out of eleven wards) to be provided with a rural road in Ijebu North Local Government Area of Ogun State, Nigeria. Three groups of stakeholders were identified (the citizens, politicians and technocrats) and four criteria were used to evaluate the wards. The result from the analysis of variance shows that there is a significant difference among the wards in terms of the four criteria used. The study devised a decision support system (DSS), using concordance/discordance analysis within a multi-criteria analysis framework, to show how compromise can be reached on the issue of which ward should be selected for road provision. The application of the DSS shows that ward ten will be selected. It is shown in this study how areas can be evaluated for infrastructure provision and the application of a conflict resolution oriented decision process to select a particular area. Keywords: Rural Roads, Decision Making Process, Multicriteria Analysis

Strategy selection for sustainable manufacturing with integrated AHP-VIKOR method under interval-valued fuzzy environment

Selection of an appropriate sustainability strategy is a multi-criteria decision making (MCDM) problem for manufacturing organizations due to incommensurate and conflicting evaluation criteria. In addition, incomplete information and different opinions of decision makers lead to uncertainties such as interval data and fuzziness. This study proposes a hierarchal MCDM method by combining Analytical Hierarchal Process (AHP) and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) methods under interval-valued fuzzy environment to deal with ranking of sustainable manufacturing strategies. Linguistic variables were used to assess the ratings of strategies and weights for selection criteria. These linguistic variables were expressed in the triangular interval-valued fuzzy sets. Using a case study of manufacturing small and medium enterprise, the final ranking of the strategies was elicited in accordance with this procedure. Subsequently, a sensitivity analysis was performed to validate the stability of the proposed final ranking. This method can be used as a decision making tool for alternative or strategy selection in other areas where uncertainties are inherent.

Application of interval 2-tuple linguistic MULTIMOORA method for health-care waste treatment technology evaluation and selection

The management of health-care waste (HCW) is a major challenge for municipalities, particularly in the cities of developing countries. Selection of the best treatment technology for HCW can be viewed as a complicated multi-criteria decision making (MCDM) problem which requires consideration of a number of alternatives and conflicting evaluation criteria. Additionally, decision makers often use different linguistic term sets to express their assessments because of their different backgrounds and preferences, some of which may be imprecise, uncertain and incomplete. In response, this paper proposes a modified MULTIMOORA method based on interval 2-tuple linguistic variables (named ITL-MULTIMOORA) for evaluating and selecting HCW treatment technologies. In particular, both subjective and objective importance coefficients of criteria are taken into consideration in the developed approach in order to conduct a more effective analysis. Finally, an empirical case study in Shanghai, the most crowded metropolis of China, is presented to demonstrate the proposed method, and results show that the proposed ITL-MULTIMOORA can solve the HCW treatment technology selection problem effectively under uncertain and incomplete information environment.

Using MACBETH method for supplier selection in manufacturing environment

Article history: Received October202012 Received in revised format December 28 2012 Accepted January2 2012 Available online 3January 2013 Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM) methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH) is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches. © 2013 Growing Science Ltd. All rights reserved

Wastewater treatment: New insight provided by interactive multiobjective optimization

In this paper, we describe a new interactive tool developed for wastewater treatment plant design. The tool is aimed at supporting the designer in designing new wastewater treatment plants as well as optimizing the performance of already available plants. The idea is to utilize interactive multiobjective optimization which enables the designer to consider the design with respect to several conflicting evaluation criteria simultaneously. This is more important than ever because the requirements for wastewater treatment plants are getting tighter and tighter from both environmental and economical reasons. By combining a process simulator to simulate wastewater treatment and an interactive multiobjective optimization software to aid the designer during the design process, we obtain a practically useful tool for decision support. The applicability of our tool is illustrated with a case study related to municipal wastewater treatment where three conflicting evaluation criteria are considered.