Multiple Attribute Decision Making Techniques Applied to Reusable Responsive Spacelift

Development of irrigation networks is a crucial element in increasing the efficiency and effectiveness of water distribution for agriculture. This research aims to determine priorities for developing irrigation networks in the Bedadung Irrigation Area, Jember Regency, using the Multiple Attribute Decision Making (MADM) method. This method consider various criteria influencing decision-making, such as physical condition of the channel, land area, water requirements, and level of infrastructure damage. This research involved collecting primary and secondary data through field surveys, interviews with interpreters, as well as reviewing technical and administrative documents related to irrigation networks. Data was analyzed using several MADM techniques, such as Simple Additive Weighting (SAW), Weighted Product (WP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to obtain the weight of each criterion and determine development priorities. The results show that the main priority for developing irrigation networks in the Bedadung Irrigation Area is repairing primary, secondary, and tertiary canals that are badly damaged, followed by increasing canal capacity to meet water needs in the dry season. Implementation of the results of this research is expected to increase the efficiency of irrigation water distribution, reduce water losses, and increase agricultural productivity.

In the present study MADM methods are used for optimization of geometrical combinations. The vortex tube is very simple thermo-fluidic apparatus which generates low temperature and high temperature air streams. The inlet fluid is tangentially compressed into the inlet nozzles of vortex tube. Thermal performance of vortex tube is noticeably influenced by its geometrical and operational parameters. In this study effect of various geometrical (L/D ratio: 15, 16, 17, 18; exit valve angle; ; cold end orifice diameter: 5,6 and , tube divergence angle: ) and operational parameters (inlet pressure: 2 to 6 bars) on the performance of vortex tube have been investigated experimentally. The best configuration of the vortex tube is chosen using Multiple Attribute Decision Making (MADM) techniques. COP for cooling and the ideal temperature difference on the cold end were used to analyse the vortex tube's performance. The WSM (Weighted Sum Method), WPM (Weighted Power Method), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and AHP (Analytical Hierarchy Process) MADM (Multiple Attribute Decision Making) methods are used. Experimental best performing combinations are obtained for Length to Diameter ratios with exit valve angle as and at orifice diameter for inlet pressure of 5 and 6 bar pressure. Best COP, efficiency and cold end temperature difference are and respectively for the combination of 15 valve angle, orifice diameter and 2 bar pressure by MADM techniques.

Hesitant interval neutrosophic linguistic sets (HINLSs) are one of the core generalization of various sets, such as neutrosophic set (NS), interval neutrosophic set (INS), and interval neutrosophic linguistic set (INLS). HINLS can represent the uncertainty, inconsistency, and reluctance of assessment specialists by expressing qualitative and quantitative information. The goal of this article is to introduce a novel MADM technique that can account for changes in the semantic environment as well as negative consequences of experts’ excessive evaluation values. First, several innovative operational rules based on Schweizer-Sklar (SS) t -norm and t -conorm and a novel comparison procedure for HINLS are established by integrating different linguistic scale functions. This allows for varied semantic settings to be handled. Then, various innovative HINL Schweizer-Sklar power aggregation operators (AOs) are suggested, containing hesitant interval neutrosophic SS power average (HINLSSPA) operator, weighted hesitant interval neutrosophic SS power average (WHINLSSPA) operator, hesitant interval neutrosophic SS power geometric average (HINLSSPGA) operator, weighted hesitant interval neutrosophic SS power geometric average (WHINLSSPGA) operator, some core properties, and various special cases of these AOs are examined. Additionally, based on the initiated AOs, a multiple attribute decision making (MADM) technique with HINL information is anticipated. Finally, a numerical example is illustrated to show the effectiveness and practicality of the anticipated MADM method. A comparison with existing approaches are also discussed.

In process systems engineering, one may encounter design problems that require choosing one among the predefined set of alternatives in a complex decision making environment. In most cases, the selection process involves multiple conflicting criteria that can be either qualitative or quantitative in nature. The use of multiple attribute decision making (MADM) technique thus has been proven effective in providing a transparent, systematic and rational approach to problem solving. In this study, a variant of the widely used MADM technique known as the Analytic Hierarchy Process (AHP) has been developed and applied for the selection of low-carbon technologies. This approach enables the selection of optimal alternative by incorporating not only the judgment of domain experts but also their degree of confidence through the use of fuzzy numbers for the pairwise comparison ratios in the AHP decision framework. The proposed fuzzy AHP then determines a set of crisp weights that maximizes the degree of consistency of all judgments taken together. The said approach can also derive crisp weights from an incomplete fuzzy pairwise comparative judgment matrix (PCJM). To illustrate the technique, a case study involving comparison of electricity storage technologies for renewable energy systems is considered. This selection problem is important due to the intermittent nature of many forms of renewable energy, which thus require cost-effective auxiliary energy storage subsystems for successful deployment.

Selection of a construction material is one of the important tasks in any construction project as it is influenced by many factors like cost, durability, eco friendliness, maintenance, availability, strengths, efficiency, etc. Initially, there is a trend where they used to consider only cost and efficiency factors in the selection of a construction material. Project executives face the difficulty to arrive at a reasonable decision considering all the other influencing factors. Different varieties of construction materials are available in the market with diverse properties; hence it becomes difficult to choose a particular type of material considering all parameters having importance. Here, we are using a simple methodology to make a selection of material on multiple attribute decision making (MADM) approach in place of the existing practice. MADM is making preference decisions (selecting, ranking, screening, prioritization, classification) over the available alternatives that are characterized by attributes. In order to select a material, a simple optimization method, Simple Additive Weighting (SAW) is used. This is also called as weighted sum method. It is the simplest and still the widest used MADM method.. By using SAW method the most suitable material can be determined. The result of this method is highly dependent on the weightages of attributes and may vary from time to time. This study will be useful as a decision making tool and for increasing the confidence in selecting the materials in big projects.

Many decision making problems of business and management are formulated in terms of Multiple Attribute Decision Making (MADM): given a set of alternatives evaluated with multiple criteria, find the alternative which according to the Decision Maker (DM), has the most preferred combination of criteria values (attributes), or rank alternatives from the most preferred one to the least preferred one. The MADM methods incorporate mechanisms of building preference models based on information obtained from the DM. In a wide variety of such methods, the DM is supposed to provide information in terms of weights of criteria, usually understood as criteria’s priorities. These weights serve as parameters of the method-pecific preference models. The DM can define weights directly, or by using special weight elicitation techniques such as AHP, MAVT and others. Our concerns are that when using weight-based methods, the DM cannot ensure the correctness of the preference model. First, different weight-based methods use different kinds of preference models, which prioritize criteria based on weights in different manners. Second, interpretation of weights in some MADM methods is far from intuitive. Thus, a situation may occur when an inexperienced DM thinks of weights differently than they actually work in the method, and expresses the preference information incorrectly. In this paper we demonstrate the differences between how weights are interpreted in several methods: simple additive weighting, TOPSIS, VIKOR and PROMETHEE. We do it by comparing rankings produced with methods based on randomly generated data. We demonstrate that differences of interpreting weights significantly contribute to differences in produced rankings. A solution to this problem could be twofold: first, increasing awareness of differences between method-specific weight-based prioritizing mechanisms, and second, providing interpretations of weights for popular methods in the language understandable by the DMs.

Decision-makers frequently use the MADM (Multiple Attribute Decision Making) method to assist in solving decision-making issues. This approach can use a variety of algorithms, including Simple Additive Weighting (SAW) and Weighted Product (WP). The challenge in this research is determining which of the SAW and WP approaches is more pertinent or acceptable for solving scenarios involving scholarship recipient selection. Five factors were taken into consideration when deciding who would receive a scholarship: academic achievement index (GPA), parents' income, past accomplishments, participation in student organizations, and the number of parents' dependents. A sensitivity test, which involves altering the weight of each test method's criterion and then comparing the percentage change between the two ways, is one method that can be used to gauge the effectiveness of the MADM method. The SAW method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.95. The WP method implementation results show that alternative nine (MHS9) has the highest preference value, which is 0.12. The total change in the findings of the sensitivity test for the SAW method is 7.64%, compared to 2.06% for the WP method. Thus, it can be inferred that the SAW approach is thought to be pertinent for addressing the issue of choosing scholarship applicants.

Water is the basis of life, the foundation of nature, and the pillar of social, economic, and cultural development of societies. So, the supply of safe and consumable water has always been a concern. On the other hand, a major challenge of modern societies is the lack of precipitation and frequent droughts. Thus, the present paper assesses the principles of water governance in the Sistan region with respect to the development of water exploitation systems with an environmental approach and presents an integrated multi-attribute decision-making model with a water governance approach in the Sistan region. The simple additive weighting (SAW) method that is used here is one of the multiple attribute decision making (MADM) methods. The indicators of water governance principles were derived from the opinions of 30 water experts, faculty members, and water users in the Sistan region by the SAW method, and weights were assigned to them to form MADM matrices. According to the results, six indicators were derived as the indicators determining the principles of water governance. ‘Traditional users’ was selected as the strongest system and ‘irrigation and drainage networks exploitation companies’ as the weakest system. Also, according to the results of water experts, the first rank was assigned to ‘irrigation and drainage networks exploitation companies’ (A2) with the final crisp score of 6.818 followed by ‘water user cooperatives’ (A4) with the final crisp score of 6.515 in the second rank and ‘private firms’ (A6) with the final crisp score of 6.308 in the third rank.

An approach using defuzzifying methods is proposed for the fuzzy multiple attribute decision-making (MADM) problems. The computing effectiveness of the proposed defuzzifying methods combined with the simple additive weighting (SAW) method and the technique for order preference by similarity to ideal solution (TOPSIS) method are evaluated based on a comparison to the improved fuzzy weighted average (IFWA) followed by a ranking method. Both SAW and TOPSIS methods are two of classic MADM methods. The purpose of this application is to make the method easier to program and data easier to manipulate. This results in a more practical method for fuzzy decisions. A numerical example and experiment are discussed to demonstrate the implementation of the methods in different input conditions.

Spectrum decision is an important functionality of a cognitive radio terminal, which allows the selection of the appropriate frequency band from the available underutilized spectrum. Spectrum decision conducts itself in accordance to the communication requirements of the secondary (or cognitive) users in the forthcoming Cognitive Radio Networks (CRNs). Selecting the best spectrum for a given transmission involves making preference decisions over the set of available alternatives of frequency bands, which are indeed characterized by different attributes. Therefore, spectrum decision can be modeled as a multiple attribute decision making (MADM) problem. In this paper, we evaluate the performance of MADM decision algorithms such as Simple Additive Weighting (SAW), Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) and the Compromise Ranking Method VIKOR for spectrum decision. The study, however, is conducted using real spectrum occupancy measurements to evaluate the performance of the aforementioned algorithms in a practical scenario. Some important attributes of underutilized spectrum are proposed for consideration in the decisions. Results show that SAW algorithm performs well for the preferred spectrum attributes in the selected scenarios, while offering a good performance also in other parameters.

The rapid development of information technology makes internet access an important requirement in many aspects. The COVID-19 pandemic has also become the basis for the increasing use of internet access, especially in the education sector. Restrictions activities outside the house, causing the productivity of students to decline. Therefore, in order to remain active and productive, students are required to follow an online learning system. This will make the use of internet quota even greater. The number of cellular providers that provide internet services sometimes makes users confused in determining which provider is better to use. In this study, the Multiple-Attribute Decision Making (MADM) - Simple Additive Weighting (SAW) methods used to identify the decision support system in determining the type of cellular provider that is the most popular among students, especially in the Griya Martubung Area. This decision support system can certainly meet the needs of internet quotas and budgets. The results show that the most popular providers are Three, followed by Telkomsel, XL Axiata, Smartfren and Indosat.

The numbers of hard disk drive heads manufactured in Thailand have increased rapidly in the past few years, and one of the most important components of the hard disk drive head is the hard disk drive arm. This component has been produced in large amounts and has been a major income source for a case study company. The manufacturing process of the hard disk drive arm, especially the machining process, is highly complicated and also a main factor of defining the usability of the final product. However, during dimension inspections, many defected parts were detected, resulting in an overall decrease in productivity, sales and profit. Normally, parts are randomly chosen from each CNC machine to be inspected. If there is a defective product, that machine would be shut down and the tool settings will be reset. If the machine that has been producing defective products is inspected late into the inspection shifts, it would result in a considerable amount of defective parts produced before any corrective actions can be made. Therefore, this study presents an application of the integration between Multiple Attribute Decision Making (MADM) and Data Mining (DM) to define the inspection order for tooling adjustment of which the machines with higher risk of producing defective parts can be inspected and corrected before those with lower risk. The methodology is as follows. First, raw measurement data from each machine was collected and noise elimination was performed using the anomaly clustering method. Secondly, K-means clustering, after a machine performance hypothesis test to confirm that the performance of each machine is not equal, was opted for dividing the raw data into three clusters, consisting of good, normal, and bad machines. Finally, a daily CNC machine priority assessment model (CNC-MPAM) is developed based on the Simple Additive Weight (SAW) technique, resulting in a machine performance score for optimal ordering of machine tooling adjustment. Experimental results suggested that this proposed method is capable of machine adjustment ordering so that defective prone machines can be serviced sooner, reducing defective parts produced and improving overall productivity.

Indonesia is a country that has a tropical climate, so that many typical tropical climate diseases emerge.This disease is caused by viruses and parasites that breed during the dry season or the rainy season.One typical tropical disease is measles.This paper discusses the geographical information system (GIS) technology by analyzing spatial data modeling to determine the classification of measles-prone areas based on immunization status coverage using the Simple Additive Weighting (SAW) and Weight Product Model (WPM) method.Some parameters are used consist of immunization status data for multiple attribute decision making (MADM), diseases preventable by immunization (PD3I), epidemic and nutritional status of infants.The SAW and WPM method in modeling spatial data analysis processes data according to the parameters to determine the scale in comparing all alternative data on the scope of classification of immunization status areas, namely: good, average, fair and poor.The test results with the Cohen's Kappa Method Consistency Test (MCT) is obtained an average coefficient of 0.41 for consistent measurements for the chosen method.It can be concluded that the two measurements using the SAW and WPM methods have a moderate for the strength of agreement category, for using in spatial data modeling on the GIS for classification of measles prone regions using MADM.

Applications of T-spherical fuzzy aczel-alsina power muirhead mean operators in identifying the most effective water purification process for commercial purpose

This experimental study investigated the physical model of a 180-degree river bend to introduce a new measure called as winged bandal-like (WBL) structure for river bed sediment management. The new structure is a combination of bandal-like (BL) and triangular vane structures. Nine different alternatives of the WBL structure, including three dimensionless vane effective lengths and three different vane angles, were tested in non-submerged and clear water conditions. A total of 18 attributes were then defined in accordance with the resulting river bed scouring and deposition. The multiple-attribute decision-making, simple additive weighting, and TOPSIS methods were employed to rank the alternatives. Baseline tests were also carried out for the BL and the impermeable spur dike (ISD) structures under similar flow conditions. Results revealed that the maximum scour depth, as the main cause of failure around the considered WBL structure, decreased by 31% compared to the scour around the ISD. The maximum deposition height behind the considered WBL structure showed an increase of 47% and 96% in comparison with ISD and BL structures, respectively. In the WBL structure, a longer, better-shaped sedimentary stack was developed along and close to the outer bank.