Technique For Order Preference By Similarity To Ideal Solution Research Articles

Recycling electric arc furnace slag through tailoring of ambient-cured alkali-activated mortar mix using hybrid AHP-GRA and TOPSIS

Utilizing Electric arc furnace slag (EAFS) as a precursor for alkali-activated mortar production reduces waste and supports alternative cement binders. Since the mix design includes multiple factors, the Taguchi DoE was employed by varying the modifier (fly ash) to precursor (EAFS) ratio (0–75% by mass), activator to precursor ratio (A/P) (0.52–0.66), sodium hydroxide (SH) concentration (8–14 M), and sodium silicate to sodium hydroxide ratio (SS/SH) (1.5–3.0). Analytic hierarchy process (AHP) weighted Grey relational analysis (GRA), and technique for order preference by similarity to ideal solution (TOPSIS), were utilized to achieve a high performing mix. Performance characteristics encompass flowability (flow%), final setting time (FST), compressive strength (f'cu), and flexural strength (f'cr). The optimized mix possessed 75% flowability, 575 min FST, 38 MPa f'cu, 16 MPa f'cr, and 3.75% water absorption. Precursor-to-modifier ratio dominates the mix design. The three mixes—optimized (M17), top-ranked (M8), and least-ranked (M1) were micro-structurally examined using powdered X-ray diffraction, X-ray fluorescence, scanning electron microscopy, energy dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy.

Safety resilience evaluation of hydrogen refueling stations based on improved TOPSIS approach

The traditional use of TOPSIS evaluation for assessing the resilience of hydrogen refueling stations results in overly one-sided outcomes and fails to identify the indicators that have a significant impact on the resilience of the stations. Therefore, this paper proposes an improved method for evaluating the safety resilience of hydrogen refueling stations based on CRITIC-DEMATEL and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The CRITIC-DEMATEL combination weighting method is employed to determine weights, thus improving the TOPSIS method. This method is then applied to assess the resilience level of hydrogen refueling stations. Then, introducing a Conditional Logistic Regression model identifies indicators with significant impact on resilience. The improved TOPSIS method enhances the reliability and accuracy of evaluation results. The Conditional Logistic Regression model provides a more accurate delineation of the impact size of indicators on the safety resilience of hydrogen refueling stations compared to traditional methods.

Evaluation of management practices in rice–wheat cropping system using multicriteria decision-making methods in conservation agriculture

In this study, we employed two multiple criteria decision-making (MCDM) methods, namely the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the Analytic Hierarchic Process (AHP), to determine the best management choice for the cultivation of wheat with a regime of conservation agriculture (CA) practices. By combining alternative tillage approaches, such as reduced tillage and zero tillage, with the quantity of crop residues and fertilizer application, we were able to develop the regime of CA practices. The performance of the regimes compared to the conventional ones was then evaluated using conflicting parameters relating to energy use, economics, agronomy, plant protection, and soil science. TOPSIS assigned a grade to each alternative based on how close it was to the ideal solution and how far away it was from the negative ideal solution. However, employing AHP, we determined the weights of each of the main and sub-parameters used for this study using pairwise comparison. With TOPSIS, we found ZERO1 (0% residue + 100% NPK) followed by ZERO4 (50%residue + 100% NPK), and ZERO2 (100% residue + 50% NPK) were the best performing tillage-based alternatives. To best optimize the performance of wheat crops under various CA regimes, TOPSIS assisted the decision-makers in distinguishing the effects of the parameters on the outcome and identifying the potential for maneuvering the weak links. The outcomes of this investigation could be used to improve management techniques for wheat production with CA practices for upscaling among the farmers.

Research on the Preference of Mobile Phone Photography in Leisure Life

The way of communication and thinking are reconstructed by mobile phone photography. Due to the advancement of technology and economy, mobile phone chips have become advanced and the quality of photography has improved. In addition to the communication function, the camera function of smartphones is more valued by consumers and mobile phone manufacturers. Apps with built-in cameras, photo editing and social websites are constantly being upgraded., and mobile phone photography and social media has been combined. The influence and interaction of digital images in social leisure makes mobile phone photography play an important role in people's communication on social websites. This research mainly analyzed the preferences of mobile phone photography in leisure, and the Evaluation Grid Method (EGM) of Miryoku Engineering was applied to extract the attractive attributes of mobile phone photography. William DuMouchel continuous Kano model was applied to summarize the evaluation factors of young users on the quality of mobile phone photography. SPSS.17 statistical software was applied for reliability analysis, and IPA satisfaction was applied as the weighted factor evaluation. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied to evaluate preference factors. The purpose of this research is to analyze the preferences of mobile phone photography in leisure life through these research methods, and also to provide a reference for the future promotion of mobile phone photography.

Modified jaya optimization and TOPSIS for determining the optimal frequency in LF-HVac

This study presents a novel approach of hybrid modified Jaya and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) optimization (MJTO) for efficiently determining the optimal frequency of low-frequency HVac lines. The proposed technique takes frequency constraints and static synchronous compensator (STATCOM) equations into the account. The objective functions in this study are the minimization of power losses, voltage deviation, and voltage stability index of transmission system. This study examines two types of objective functions: the traditional quadratic function and the enhanced quadratic function. These functions are used to incorporate more accurate modeling that considers low frequency. The MJTO is employed for global searching and gradient-free optimization to determine optimal control settings. The Modified Newton-Raphson method is utilized to minimize the mismatch power between power flow (PF) and STATCOM equations. The proposed method utilizes a hybrid technique to handle inequality constraints by preserving feasible solutions while keeping the original objective function intact. The suggested methodology is successfully implemented in extensive benchmark testing of IEEE systems on the 39 Bus and 14 Bus. The optimal solutions obtained are validated by comparing them to recent algorithms as mentioned in literature. The analytical and Statistical results indicates that the proposed optimization strategy is more optimistic for the LF-HVac system.

Evaluating water resource carrying capacity in Pearl River-West River economic Belt based on portfolio weights and GRA-TOPSIS-CCDM

Research on the spatial differences in the water resource carrying capacity (WRCC) and their causes can effectively address the imbalance of water resources and enhance the economic, social, and ecological properties of the basin. Sixteen cities in the Pearl River-West River Economic Belt (PR-WR EB) were selected for this study from 2017 to 2021. Based on the theoretical Driving-Pressure-State-Impact-Response model and related research, an evaluation model for WRCC was constructed. The weights obtained from the entropy method and CRITIC method were combined and assigned using the geometric method, after which they were applied to a model that combines the grey relational analysis (GRA), technique for order preference by similarity to ideal solution (TOPSIS), and coupling coordination degree model (CCDM) to calculate the evaluation value of the WRCC subsystem. Meanwhile, the spatial variability and spatial correlation of WRCC were analyzed using the natural breakpoint method, Moran's index, clustering characteristics, and outlier index. The overall WRCC of the PR-WR EB showed stable characteristics from 2017 to 2021. In terms of spatial correlation, significant spatial clustering characteristics were observed. The subsystem coupling degree ranged between 0.6 and 1.0 for all subsystems, thus exhibiting good coupling efficiency; meanwhile, the coordination degree was low and ranged between 0.17 and 0.36.

A probabilistic performance-based analysis approach for a vibrator-ground interaction system

There is an increasing interest in investigating the effects of input uncertainties on dynamic systems. The probabilistic analyses for a vibrator-ground (VG) interaction system are rare and the effects of system uncertainties need to be revealed. This study aims to present an approach for the probabilistic performance-based analysis of the VG system under multi-source uncertainties. The probabilistic model of the VG system is constructed on the basis of the Monte Carlo (MC) simulation combined with the Latin Hypercube Sampling (LHS) method, while the artificial neural networks optimized by the genetic algorithms are employed to reduce the large computational expenses in the MC simulation. Then, a multi-criteria sensitivity analysis is presented by using a technique for order preference by similarity to ideal solution (TOPSIS) to evaluate the effects of input uncertainties on the dynamic performance of the vibrator. Finally, a probabilistic simulation analysis of the VG system is conducted by implementing the presented approach. The results demonstrate the effectiveness of the presented probabilistic performance-based analysis approach for the VG system and evaluate the effects of input uncertainties on the dynamic performance of the system.

SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN KUALITAS DEPOT AIR MINERAL ISI ULANG MENGGUNAKAN METODE TOPSIS (TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION)

The Decision Support System (DSS) for determining the quality of mineral water depots using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is an application designed to assist mineral water depot managers in selecting the best mineral water supplier based on certain criteria. The TOPSIS method is used to solve multi-criteria problems by considering the relative proximity to ideal solutions and anti-ideal solutions. First, relevant criteria for assessing the quality of mineral water are selected, including physical, chemical, and microbiological parameters. Then, mineral water quality data from various suppliers is processed and normalized. Next, the normalized decision matrix is used to calculate the ideal solution and anti-ideal solution matrices. After that, a relative closeness score for each supplier is calculated based on the Euclidean distance to the ideal and anti-ideal solutions. The results of the TOPSIS analysis are used to provide recommendations for the best mineral water suppliers. By using this system, mineral water depot managers can optimize supplier selection based on predetermined quality criteria, thereby increasing customer satisfaction and maintaining the reputation of the mineral water depot in the market.

A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts

In this study, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow for the ranking of “agents”, “opinions”, etc., all defined in a very broad sense. We aim toward any process which should a priori demand or lead to some consensus in order to attain the presumably best choice among many possibilities. In order to specify the framework, we discuss previous attempts, recalling trivial means of scores—weighted or not—Condorcet paradox, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), etc. We demonstrate, through geometrical arguments on a toy example and with four criteria, that the pre-selected order of criteria in previous attempts makes a difference in the final result. However, it might be unjustified. Thus, we base our “best choice theory” on the linear response theory in statistical physics: we indicate that one should be calculating correlations functions between all possible choice evaluations, thereby avoiding an arbitrarily ordered set of criteria. We justify the point through an example with six possible criteria. Applications in many fields are suggested. Furthermore, two toy models, serving as practical examples and illustrative arguments are discussed.

Analysis comparison model of ROC-TOPSIS, ROC-WP, and ROC-Electre methods for supporting the funding decision to micro-enterprises Indonesia

Micro-business is an essential business unit that supports the economies of countries in the world, including Indonesia. Unfortunately, micro-entrepreneurs often find difficulties to obtain financial assistance from government to develop their businesses. In Indonesia, the smallest number of micro industries can be found in West Papua Province, where one of the underdeveloped areas in the province is the Sorong City. Therefore, a study was conducted to determine the application of decision support methods in selecting micro-enterprises in Sorong that are eligible for business funding. The decision support method chosen is the collaboration between the Rank-Order Centroid (ROC) method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weight Product (WP), and Elimination Et Choix Traduisant la Realite (Electre). With the analysis conducted on 10 samples of micro-enterprises in Sorong City, it was found that the micro-enterprises that were most eligible to receive assistance is Raya Helm based on ROC-TOPSIS, ROC-WP, and ROC-Electre. Then, sensitivity analysis results the ROC-Electre as the best method with the highest sensitivity percentage. Therefore, the implementation of these methods for supporting the funding decision to micro-enterprises in Sorong was successfully carried out with the output being the micro-enterprise rating results.

Twist-related parametric optimization of Joule heating-triggered highly stretchable thermochromic wrapped yarns using technique for order preference by similarity to ideal solution

Abstract A scalable approach for manufacturing highly stretchable thermochromic wrapped yarns has been reported previously. Herein, the effects of twist-related technological parameters, namely, wrapping density and outer-inner twist ratio are investigated and have been optimized by technique for order preference by similarity to ideal solution (TOPSIS). The results indicate that the preparatory twist-related parameters have a remarkable effect on the spiral geometrical configuration of yarn constituents, and thus in turn influencing the final tensile and elastic properties of wrapped yarns. The wrapping density of 800 T·m−1 and outer-inner twist ratio of 1.25 were considered as the optimal alternative using TOPSIS. Moreover, a negative relation between voltage and color-changing time of yarn spun with optimal parameters was established. It was also found that the color of yarn above elevated triggered voltages always switched from purple to pink but followed different color-changing paths. More importantly, thermochromic response of yarn is insensitive to the applied strain.

Helical airfoil corrugated tubes: A numerical comparison with common corrugated profiles and geometrical optimization by multi-objective algorithm

In this study, helical airfoil corrugated tube (HACT) has suggested to improve the heat transfer capabilities of the tube heat exchanger. Firstly, thermal-hydraulic performance of HACT is numerically compared with common helical corrugated tube (HCTs) such as helical semi-ellipse corrugated tube (HSECT), helical semi-circle corrugated tube (HSCCT) and smooth tube based on thermal performance parameters: Nusselt number (Nu), friction factor (f) and performance evaluation criteria (PEC). Helium under high Reynolds number (Re) is the working fluid of this study. By analyzing the numerical outcomes, it is found that HACT has the heat transfer coefficient roughly 4 % higher than that of HSECT, around 5 % higher than that of HSCCT and more than 60 % higher than that of smooth tube. Then, a multi-objective optimization (MOO) is carried out to optimize the geometrical configuration of HACT. Initially, a numerical experimental design is constructed using the Box-Behnken method within the response surface methodology (RSM), focusing on two objectives and three factors. Subsequently, significant regression models (SRM) are derived via analysis of variance (ANNOVA). Then, leveraging these significant regression models of Nu and PEC, the geometric optimization of HACT is executed using Non-dominated Sorting Genetic Algorithm (NSGA-II), ultimately leading to the attainment of the Pareto front. Finally, based on Pareto optimal set, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied for decision-making involving multiple objectives.

Wavelet denoising based on comprehensive index optimization and improved L2 regularization for load identification

Load identification, as an inverse problem, is still one of the challenges in the field of vibration engineering. In this paper, a comprehensive load identification method combining entropy weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) noise reduction evaluation algorithm and improved L2 regularization method is proposed to improve the load identification accuracy from the following two perspectives. Firstly, the entropy weight TOPSIS method is used to evaluate the wavelet denoising scheme comprehensively, and the optimal denoising scheme is found to reduce the noise interference in the process of inverse problem solving. Secondly, we introduce a new regularization filter function, and search for the regularization parameters by Generalized Cross-Validation (GCV) criterion and one-dimensional optimization algorithm to improve the ill-posedness of the inverse problem. Finally, the simulation and experimental verification of single-source load identification are carried out with the scaled crankcase model, while the accuracy is compared with the Tikhonov regularization method. The results show that the integrated algorithm proposed in this paper can improve the accuracy of load identification while overcoming the inadequacy of inverse problem. Unlike previous studies, the comprehensive evaluation method of denoising effect introduced in this paper provides a way to judge the denoising effect in practical engineering, and the experimental model is closer to practical engineering structures, which shows potential engineering application value.

Characteristics of Urban Flood Resilience Evolution and Analysis of Influencing Factors: A Case Study of Yingtan City, China

Intense climate change and rapid urbanization have increased the risk of urban flooding, seriously affecting urban economic and social stability. Enhancing urban flood resilience (UFR) has required a new solution to cope with urban flood disasters. In this study, taking Yingtan city as an example, a system of indicators for evaluating UFR was constructed, with 17 representative indicators, comprising three subsystems: socio-economic, ecological, and infrastructural. A hybrid model combining Fuzzy Analytic Hierarchy Process (FAHP), Entropy Weight Method (EWM), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied, to develop an index-based measurement to compare and evaluate UFR, and Gray Relational Analysis (GRA) was used to discover the main factors affecting UFR. In addition, the natural discontinuous method was innovatively used to divide the UFR grade interval into levels, and the grade change was evaluated based on the TOPSIS method. The results showed that (1) From 2010 to 2022, the UFR in Yingtan City increased by 80.69%, and the factors affecting UFR were highly correlated with urban infrastructure development; however, the ecological resilience in the subsystem showed a fluctuating downward trend because of the influence of the surface area of lakes and rivers; (2) The grades of UFR for Yingtan City increased from Level III (2010 and 2016) to Level IV (2022), with local financial expenditures and the age structure of the population being the main factors currently limiting the development of UFR. The study provides a theoretical basis for the construction of an indicator system for assessing the UFR of Yingtan and proposes practical improvement directions for UFR.

Optimal design of colour formulation prediction for cotton fabrics based on NSGA‐II and TOPSIS

AbstractThe prediction of colour formulation is an important step in reproducing the target colour. At present, there are relatively few researches on multi‐objective colour formulation problem, and the colour matching accuracy needs to be improved. In this research, a multi‐objective evolutionary meta‐heuristic method based on the Fast and Elitist Multi‐objective Genetic Algorithm (NSGA‐II) was proposed to predict the target colour recipes. The method used dye concentration as a variable and included three objective functions: (1) minimising the CMC (Colour Measurement Committee) colour difference between the formulation colour and the target colour, (2) minimising the metamerism index, and (3) minimising the cost of the formulation. The algorithm could obtain the Pareto optimal solution set after iteration. On this basis, the best combination of formulations was selected from the optimal solution set by combining the Expert Scoring Method (ESM), Entropy Weight Method (EWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The prediction effect of the model was evaluated by taking cotton fabrics and reactive dyes actually used in plant as examples. The results showed that 87.5% of the formulations met the CMC colour difference value of no more than 1, the metamerism index of 90.0% of the formulations did not exceed 1, and the cost of 92.5% of the formulations was reduced relative to the maximum extent in the Pareto optimal solution set. Further studies should be focused on removing duplicate individuals to give better diversity in the Pareto optimal solution set.

Application of Interval Valued Intuitionistic Fuzzy Uncertain MCDM Methodology for Ph.D Supervisor Selection Problem

The selection of Ph.D (Doctor of Philosophy) supervisor is always a vital and interesting problem in academia and especially for students who want to carry out Ph.D. Nowadays, selecting a supervisor for Ph.D in a scientific manner becomes a challenge for any student because of the variety of options available to the scholar. In this context, the present study aims to formulate a model for Ph.D. supervisor selection from the offered alternatives in an academic institute. A hybrid multi-criteria decision making (MCDM) framework has been applied to select the suitable supervisor of the student’s preferred criteria under interval-valued intuitionistic fuzzy (IVIF) scenario. The IVIF Analytic Hierarchy Process (AHP) has been employed to prioritize the criteria, whereas IVIF Technique for order preference by similarity to ideal solution (TOPSIS) technique is engaged to rank the available supervisors based on criteria weight. A set of eight criteria and five alternatives have been considered for modeling the problem. Moreover, the potential criteria are weighted and ranked by the multiple decision makers in the present study. To examine the consistency and robustness of the proposed integrated approach, sensitivity analysis and comparative analysis have been carried out. From all the analyses, it can be conferred that the suggested approach is quite useful to apply in different decision-making scenarios.

Decision Support System For New Employee Selection Using AHP And TOPSIS

There are so many prospective workers with the same educational background, but not necessarily in accordance with the required company position and not necessarily they have the same expertise. To minimize the occurrence of errors, it can be done by making a decision-making system (DSS) to provide these recommendations. In this study, the Analytical Hierarchy Process (AHP) and the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method were used to provide recommendations for prospective new employees. The steps taken are to compare the importance of each criterion weight with the AHP method. Then the ranking stage is carried out using the TOPSIS method to get recommendations for selected employees. The data used in this study is primary data in the form of 70 data on prospective employees from PT Hutama Jaya Perkasa. From the 70 data then selected to be 36 prospective employees based on the order of the highest ranking. Software testing is done by comparing the results of system calculations and the results of company calculations. Based on the test results obtained an accuracy value of 94.4%.

Green Transition Assessment, Spatial Correlation, and Obstacles Identification: Evidence from Urban Governance Data of 288 Cities in China

The green transition of China’s cities is crucial for ecology civilization realization. Based on the driver–pressure–state–impact–response (DPSIR) framework, an integrated technique for order preference by similarity to ideal solution (TOPSIS) model with entropy weight, this study achieved the comprehensive assessment of the green transition of 288 province-level municipalities and prefecture-level cities in China over 18 years from 2002 to 2019, in addition to the spatial correlations and obstacles analysis. The results indicate that major cities in China have a more significant green transition value, and the eastern region is developing fast, while the northeast region is relatively slow. There was heterogeneous spatial distribution for green transition, because of the disequilibrium sustainable development of 288 cities. Green transition has a significantly positive spatial autocorrelation in the cities of China, the high–high significant clusters greatly increased, and the main locations changed from the northeast to southeast of China. Frequent obstacles were also found, including road infrastructure construction, water resources, and the green coverage of urban built-up areas. Based on these results, several policy implications were put forward, including the optimization of environmental laws and regulations, the development of green transportation infrastructure, resource conservation and the circular economy, the establishment of a green financial system, and increasing the linkage for the green transition of different cities.

Multi-objective modeling and evaluation for energy saving and high efficiency production oriented multidirectional turning considering energy, efficiency, economy and quality

To promote energy saving, high efficiency and quality production in the mechanical manufacturing industry, a large number of studies have been conducted on modelling and evaluation. However, most of the approaches have focused on single objective modelling, evaluation and conventional machining method like unidirectional turning (UDT). This paper presents a multi-objective modelling and evaluation method for energy, efficiency, economy and quality using a new process of forward-and-reverse multidirectional turning (MDT). Firstly, the multi-objective influential factors of cutting parameters for energy consumption, cutting time, production cost and surface roughness of MDT are analyzed to establish the corresponding models, respectively. Then taking the energy consumption, cutting time, production cost and surface roughness as the objectives, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied for the multi-objective evaluation through different processes. Finally, the case study shows the practicability of the MDT method and evaluation method for energy optimization and energy conservation.

Numerical simulation and multi-objective optimization of thin-walled aluminum/carbon fiber reinforced plastic hybrid tubes under axial crushing

Crushing behavior analysis and energy absorption optimization are crucial for lightweight structures in automotive applications. The present paper aims to investigate the crushing behavior of thin-walled aluminum/CFRP hybrid tubes under axial loading using an explicit finite element (FE) simulation. The damage constitutive models of aluminum and CFRP are implemented by coding the user-defined subroutine VUMAT in ABAQUS/Explicit, which includes the damage initiation and evolution laws and element deletion scheme. Parametric studies are conducted to assess the effects of radius and aluminum layer thickness on the crushing performance of hybrid tubes. Additionally, a multi-objective optimization is performed on the Isight platform using a non-dominant sorting genetic algorithm (NSGA-II) and technique for order preference by similarity to ideal solution (TOPSIS) with entropy weight method. The optimization aims to maximize crashworthiness and increase energy absorption capacity, enabling designers to select an optimum size ratio.