Technique For Order Of Preference By Similarity To Ideal Solution Method Research Articles

Application of hybrid multi-criteria decision-making approach to analyze wastewater microalgae culture systems for bioenergy production

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that "Pediastrum sp. &Micractinium sp." was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

Enhancing EDM performance with multi-objective decision-making using copper-coated aluminum electrodes and TOPSIS methodology for Ti-6Al-4V machining

The exploration of Electrical Discharge Machining (EDM) with coated electrodes represents a relatively novel research avenue, thereby yielding limited published research outcomes. The choice of coating material plays a pivotal role in the EDM machining process, and alterations in coating materials can directly influence the adjustment of technological parameters in EDM. Consequently, research dedicated to optimizing these technological parameters for EDM employing coated electrodes is of paramount importance, and it promises to advance the practical implementation of this cutting-edge technique. In this study, we systematically investigate the technological parameters for EDM employing a copper-coated aluminum electrode in the context of Ti-6Al-4V machining. Our research outcomes are framed within a multi-objective optimization paradigm, with a focus on Material Removal Rate (MRR) and Surface Roughness (SR) as vital quality indicators. To address the intricate multi-objective optimization challenge, we have harnessed the combined power of the Taguchi methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The amalgamation of these techniques enables us to navigate the complexities of EDM parameter optimization effectively. Our findings reveal that the most favorable process parameters entail a configuration of [Formula: see text][Formula: see text]V, [Formula: see text] A, [Formula: see text][Formula: see text][Formula: see text]s, resulting in an MRR of 0.028[Formula: see text]mg/min and an SR of 7.56[Formula: see text][Formula: see text]m. These optimized parameters exemplify a substantial enhancement in machining efficiency and surface quality when utilizing coated electrodes. Moreover, our study scrutinizes the quality of the machined surface under optimal conditions with coated electrodes. We employ the TOPSIS method as a proficient solution for this endeavor, offering a straightforward approach to this intricate calculation process.

A novel Zende’s-TOPSIS method towards estimation of measurement uncertainty in hole diameters

The ‘Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)’ is one of the best methods for ‘Multi-Criteria Decision-Making’ and ‘Multi-Objective Optimization’. The traditional TOPSIS method determines the best alternative under fixed conditions. However, it cannot determine the best upper limit and lowest limit values. This work explains the detailed methodology of the newly developed Zende’s-TOPSIS method which was used to estimate the measurement uncertainty in hole diameters. Four identical holes and one center hole in an industrial component were measured to investigate measurement uncertainty. According to the experimental results, Zende’s-TOPSIS method performed better than the traditional TOPSIS method. The percentage improvement in the Zende’s-TOPSIS method over the traditional TOPSIS method ranges from 0.0209% to 0.3053%. Using Zende’s-TOPSIS method, the percentage maximum measurement uncertainty for four identical holes varies from 0.8067% to 1.0222%, whereas for the center hole, it varies from 0.5261% to 0.5576%. Similarly, the percentage minimum measurement uncertainty for four identical holes varies from 0.3839% to 0.6406%, whereas for the center hole, it varies from 0.4014% to 0.4041%. The proposed method is also capable of estimating the machined tolerances of the component, which ranges from 18.0772 mm to 18.1708 mm for four identical holes and 49.2215 mm to 49.2572 mm for the center hole. The proposed method can solve various ‘Multi-Objective Optimization’ problems.

Performance evaluation and optimal design for passive turbulence control-based hydrokinetic energy harvester using EWM-based TOPSIS

Passive turbulence control (PTC) in the form of square-shaped rods (SSR) is applied to improve the performance of the flow-induced vibration (FIV)-based energy harvester. The influence of SSR installation positions (θ) on the mechanical power and hydroelastic efficiency of SSR-cylinders is studied experimentally. Vortex-induced vibration (VIV) and VIV-galloping coupling modes are observed in this research. It is found that the SSR-cylinder with θ = 150° (VIV-galloping coupling) achieves the highest mechanical power, while the SSR-cylinder with θ = 180° (VIV) attains the highest hydroelastic efficiency. To evaluate the performance of energy harvesting and find the optimal design of the oscillator, the technique for order of preference by similarity to ideal solution (TOPSIS) is employed. The TOPSIS method considers both the average and maximum values of mechanical power and hydroelastic efficiency, with data-driven and adaptive weights estimated using the entropy weight method (EWM). It is indicated that the SSR installed at 150° obtains the optimal performance in a wide flow velocity range, followed by 140° and 70°. Finally, the effectiveness of the optimal design is validated by comparing it with other harvesters and the rationality of the proposed EWM-based TOPSIS method is analyzed in detail.

Multi-objective optimization of twisted tri-lobed tube geometry for enhanced heat transfer and reduced resistance in turbulent flow

This study presents a detailed multi-objective optimization analysis of turbulent flow and heat transfer within a twisted tri-lobed tube, employing an integrated approach that combines Central Composite Design (CCD), Response Surface Methodology (RSM), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto frontier analysis, Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The investigation focuses on optimizing key design parameters: Reynolds number (Re), twist pitch (P), and minor circle radius (r), targeting Nusselt number (Nu), Poiseuille number (fRe), and Performance Evaluation Criterion (PEC) as optimization objectives. Our major findings reveal that the developed second-order regression model precisely predicts the influences of these parameters on Nu, fRe, and PEC, with sensitivity analysis showing Re's strong positive impact on Nu and fRe, P's negative effect on fRe, and r's minimal impact. The study notably highlights the significant Nu enhancement with Re increase. Utilizing multi-objective optimization, we identified a Pareto optimal set, and through LINMAP and TOPSIS methods, derived compromise solutions that optimally balance heat transfer efficiency, flow resistance, and overall performance. These outcomes underscore the critical importance of parameter selection to meet specific engineering needs, offering a strategic framework for enhancing twisted tri-lobed tube designs.

A life cycle decision framework of China offshore wind turbines with ANP-Intuitionistic fuzzy TOPSIS method

In China, offshore wind energy is a popular source of green energy. Selecting offshore wind turbine design schemes is a decision problem based on multiple criteria. However, the selection is hardly made from the point of view of the life cycle due to the complex association of evaluation criteria, especially in the conceptual design stage. To solve this problem, a new multi-criteria decision-making framework for selecting the life cycle design scheme of offshore wind turbines is designed. The design information of the life cycle process of these turbines is expressed using Function-Structure-Material-Process-Transportation model in this framework. The life cycle evaluation index system of offshore wind turbines was established and mapped with this model to carry out rapid evaluation of various schemes. In light of this, an intuitive fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method based on analytic network process (ANP) was proposed to process fuzzy decision information and establish criteria correlation. Finally, a case study was conducted, and sensitivity and comparative analyses were carried out. The proposed method can effectively select the optimal scheme from six different design schemes for the life cycle of offshore wind turbines.

Experimental investigation on titanium alloys for machining of stepped circular holes using ultrasonic-assisted hybrid ECM

In the recent development of high-performance gas turbine engine, there is a tendency to design the cooling holes in order to improve the heat transfer and cooling efficiency. Titanium alloy is the most preferred material for these blades. It is hard material, and hence, the traditional drilling is not appropriate for “Ti” alloy. This research presents the design and optimization required to manufacture contoured holes on a titanium-based superalloy using hybrid electrochemical machining (ECM) under different operating conditions. The circular holes are developed and are analyzed by ANOVA. The experimental results are further optimized using a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The voltage (V), feed rate (f1), and feed rate (f2) were identified as the most influencing factors which are further used for stepped circular hole machining. A design of the experiment is also optimized using the TOPSIS method. The obtained experimental results are verified using a SEM analysis to confirm the uniformity of the machined surfaces and the inverse relationship of the overcut with the increasing values of the voltages and feed rates. Optimal machining conditions for the stepped hole machining were determined for voltage 18 V, feed rate “f1” at 0.8 mm/min, and feed rate “f2” at 1.35 mm/min.Graphical

Novel Multi-Criteria Group Decision Making Method for Production Scheduling Based on Group AHP and Cloud Model Enhanced TOPSIS

Optimized production scheduling can greatly improve efficiency and reduce waste in the steel manufacturing industry. With the increasing demands on the economy, the environment, and society, more and more factors need to be considered in the production scheduling process. Currently, only a few methods are developed for the comprehensive evaluation and prioritization of scheduling schemes. This paper proposes a novel MCGDM (multi-criteria group decision making) method for the ranking and selection of production scheduling schemes. First, a novel indicator system involving both qualitative and quantitative indicators is put forward. Diverse statistical methods and evaluation functions are proposed for the evaluation of quantitative indicators. The evaluation method of qualitative indicators is proposed based on heterogeneous data, cloud model theory, and group decision-making techniques. Then, a novel Group AHP model is proposed to determine the weights of all evaluation indicators. Finally, a novel cloud-model-enhanced TOPSIS (technique for order of preference by similarity to ideal solution) method is proposed to rank alternative production scheduling schemes. A practical example is presented to show the implementation details and demonstrate the feasibility of our proposed method. The results and comparative analysis indicate that our hybrid MCGDM method is more reasonable, flexible, practical, and effective in evaluating and ranking production scheduling schemes in an uncertain environment.

Conflicts due to cultural differences in multicultural ships

ABSTRACT The growth in global trade and technological developments in the maritime industry have increased the number of ships and their capacities. Despite the decreased size of crews in modern ships, the increased number of ships has increased the demand for qualified seafarers. Shipowners and ship operators have tried to solve the problem of this imbalance by employing seafarers, not only from their own countries, but also from other countries. Increased competition and costs have increased the number of multinational crews in the maritime trade. In ships operated with multinational crews, potential conflicts among the crewmembers due to cultural differences endanger the safety of the ship and the cargo. In this study, the literature was examined to identify conflicts due to cultural differences in multinational ships. The factors causing conflict were established as criteria by taking the opinions of human resources experts of eleven maritime enterprises and four academics, and the criteria weights were determined with the fuzzy AHP (analytic hierarchy process) method. The rankings of solution alternatives were calculated by the fuzzy TOPSIS (technique for order of preference by similarity to ideal solution) method.

Establishment and application of drug utilization evaluation applying the weighted TOPSIS method: A study based on real-world data of tislelizumab.

How to comprehensively evaluate the rationality of drug use is a challenging issue. To establish the evaluation index of the effective use of tislelizumab, so as to ensure its higher rationality and normalization in clinical application. Based on the indications, drug instructions, and relevant guidelines of the National Basic Medical Insurance Restriction Catalogue, a retrospective analysis and evaluation of 286 cases of using tislelizumab injection in our hospital from January to December 2022 were conducted using the weighted technique for order of preference by similarity to ideal solution (TOPSIS) method. Among the 286 medical records evaluated, the main irrational manifestations were inappropriate indications (90 cases, 31.47%), auxiliary examination and laboratory examination did not meet the minimum requirements of combination chemotherapy drugs (40 cases, 13.99%), the drug course was not standard (39 cases, 13.64%). Among the included cases, 57.34% were reasonable cases (Ci⩾ 0.8), 10.84% were basic reasonable cases (0.6 ⩽Ci< 0.8), and 31.82% were unreasonable cases (Ci< 0.6). The TOPSIS method, with its attribute hierarchical model (AHM)-weighted approach, can be employed as the rational assessment technique for the injection of tislelizumab. The clinical application of tislelizumab in our hospital is still insufficient, which needs to be further improved management.

A study on Analysing the Selection of Materials for Knee Implant Femoral Components using the TOPSIS method

Specialists are creating more sophisticated and useful materials daily as technology advances. For orthopaedic implants such as "knee replacements, hip replacements, and orthopaedic accessories", biomaterials are employed to produce prosthetic organs. In patients with severe osteoarthritis (OA) of the knee, "total knee replacement (TKR)" is one of the most successful surgical procedures for pain management and functioning rehabilitation. Humans continue to experience issues with the kneecap, such as aseptic dislocation brought on by excessive wear across articular surfaces, stress-shielding of the bone by prostheses, and soft tissue formation at the junction of implanted bone. due to improper “TKR material selection”. Since selecting the best materials for the femoral component of TKR requires careful consideration, the "technique for order of preference by similarity to ideal solution (TOPSIS)" is used in this research paper. This technique uses an order of preference based on how closely the preferred option is to the ideal solution. The "equal weights method (EWM)" assigns various criteria distinct weights of importance. The rank of alternatives using the TOPSIS method for “Co-Cr-Mo is fourth, Co-Ni-Cr-Mo is third, NiTi SMA is first, Porous NiTi SMA is second, pure Ti is sixth and Ti-5Al-2.5Fe is fifth”. The result indicated that FC material using TKR Nickel Titanium Shape Memory Alloy (NiTi SMA) is at rank 1 with properties such as Tensile Strength 960 MPa, Density 6.45 g/cc, extremely high Corrosion resistance, and exceptionally high Wear resistance.

TOPSIS method based on connection number of set pair analysis subject to bipolar fuzzy environment with application in decision making

In this manuscript, we develop TOPSIS (Technique for order of preference by similarity to ideal solution) method in the setting of bipolar fuzzy environment which has the ability to deal the data while keeping in view the positive and negative aspects. By using bipolar fuzzy sets, we establish the novel concept of rating the numerous preferences of any object described through the connection number(CN) of set pair analysis(SPA). In this regard, we extend the TOPSIS method based on the connection number(CN) of set pair analysis(SPA) in the frame of bipolar fuzzy sets. For the sake of verification, effectiveness and superiority of our method, we conduct the comparative study of some real life problem related to decision making theory. Moreover, we observe that our proposed method also fulfills the existing test criterions.

Pioneering Heat Exchanger Network Synthesis: A TOPSIS Driven Paradigm for Optimal Solutions

Multi-Criteria Decision Making (MCDM) is a significant challenge across various domains, requiring adept resolution of conflicts arising from diverse objectives and criteria. This study proposes an innovative approach aimed at optimizing controllability, minimizing irreversibility, and maximizing overall effectiveness in control system design to address this challenge. The primary objectives of this study are to introduce a novel methodology for selecting Heat Exchanger Networks (HEN) using the well-established Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Additionally, a closeness coefficient is introduced to rank alternatives networks based on their proximity to the ideal solution. Two illustrative case studies are presented to showcase the methodology's effectiveness, adaptability, and robustness in discrete multi-criteria decision-making problems, particularly in the context of HEN selection. Consistently identifying HEN configurations that fulfill controllability objectives, the methodology demonstrates its effectiveness and potential for broader applications beyond HEN optimization. The case study results affirm the adaptability and robustness of the proposed approach. In summary, this paper introduces an original and versatile approach to address the complexities of multi-criteria decision-making, specifically in the context of HEN selection. Rooted in the TOPSIS method and fortified by the closeness coefficient, the methodology holds promise for intricate decision-making processes and offers transformative possibilities for control system design. The study concludes by inviting further exploration of the proposed methodology, emphasizing its significant contribution to the field and its potential for widespread impact. Researchers and practitioners are encouraged to investigate and apply this innovative approach in diverse decision-making scenarios. The ranking results reveal that alternatives M and K is the optimum one among all the alternatives for both cases with a closeness coefficient equal to 0.651 and 0.971.

A Multi-objective integrated approach to address sustainability in a meat supply chain

Many supply chains have taken action to consider the principles of sustainability in their business over the past two decades. However, addressing sustainability is still a challenge due to imposing some restrictions. This could be more challenging in a food supply chain because of consuming a large amount of natural resources and its connection to public health. Regarding this significance, this research develops a mechanism to integrate all the primary functions of a meat supply chain given three pillars of sustainability: (i) cost, (ii) social aspect, and (iii) environmental aspect. To this end, we develop a three-objective mathematical formulation to integrate supplier selection, production planning, and product distribution in a meat supply chain. This study also identifies criteria representing suppliers’ impact on the environment and utilizes a Stochastic Analytic Hierarchy Process (SAHP) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods to gauge that impact and evaluate suppliers’ scores. Furthermore, a solution method is designed based on the Normalized Normal Constraint method to generate Pareto-optimal solutions. Lastly, we apply the developed mathematical formulation and the solution methodology using a numerical study inspired by a real case in Ontario, Canada. The results demonstrate that the developed solution methodology can generate diverse and practical Pareto-optimal solutions in which social and environmental aspects could be improved significantly by incurring a minor extra cost.

Analysis of factors and strategies for the implementation of sustainable tourism in a green economic structure in China

The tourism industry significantly contributes to the economic development of numerous emerging countries by facilitating the expansion of local enterprises. However, tourism may adversely affect the environment, local communities, and cultural heritage when it is not managed effectively. In this study, the case of Guilin city of China is undertaken for the analysis. Guilin, a popular tourist destination in southern China, has experienced rapid growth in tourism, generating economic benefits but also posing challenges related to environmental sustainability and social impact. This study uses Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify the most important criteria, sub-criteria, and effective policy strategies for promoting sustainable tourism in developing economies. Therefore, the study identified five criteria, twenty sub-criteria, and six policy strategies for sustainable tourism development in Guilin, China. The results of Fuzzy AHP method has identified economic viability, infrastructure and services, and social and cultural impact are the most suitable criteria for sustainable tourism. The results of Fuzzy TOPSIS method has recognized community-based tourism, sustainable tourism certification, and public-private partnerships as most effective strategies. This research provides useful insights for policymakers and stakeholders, enabling them to contribute to the sustainable development of the tourism industry and support the achievement of the United Nations sustainable development goals.

Implementation of Discrepancy Evaluation Application Based on TOPSIS-TTA

One of the developments in the field of educational evaluation utilized as an evaluation tool to identify the key elements that drive the success of blended learning is the TOPSIS-TTA-based Discrepancy evaluation application. This evaluation application combines the TTA (Tat Twam Asi) concept, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, and the Discrepancy evaluation model concept. The purpose of this study is to demonstrate the implementation outcomes of the TOPSIS-TTA-based Discrepancy evaluation application at IT vocational schools in Bali, as well as the results of usage trials, final product revisions, and its dissemination. The research method used focused on the usage trial stage, final product revisions stage, dissemination stage, and implementation stage. The usage trials comprised 39 respondents, while the application test involved 150 participants. For the final product revisions, three research team members were engaged, along with 150 respondents during the dissemination activity. The assessment instruments employed during the trial usage and application testing were questionnaires. Bali’s IT vocational schools served as the study’s location. The study’s data analysis method was descriptive quantitative by converting the results of the application effectiveness percentage which has been compared with the standard effectiveness scale of eleven. The findings of this investigation suggest the effectiveness level of evaluation application including the advanced category, so that in general the evaluation application is ready to be implemented on a wide scale in the field. The significance of this study in the field of educational evaluation lies in its ability to simplify the process for evaluators in choosing high quality evaluation tools, relying on dependable trials of application implementation and usage.

Hydrothermal synthesis of Fe3O4 nanoparticles at different pHs and its effect on discoloration of methylene blue: Evaluation of alternatives by TOPSIS method

In this study, hydrothermal synthesis was employed to produce Fe3O4 nanoparticles for the methylene blue removal from an aqueous medium. The production of magnetite nanoparticles involved the utilization of Fe2+ and Fe3+ salts, and their respective solutions were created at pH levels of 10, 11, and 12, subsequently subjected to autoclave treatment. The evaluation of pH-induced variations in nanoparticle characteristics was conducted through X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Field emission scanning electron microscopy (FESEM), vibrating-sample magnetometer (VSM), and Dynamic light scattering (DLS) analyses. pH levels within the synthetic medium yielded diminutive Fe3O4 nanoparticles characterized by augmented saturation magnetization, heightened zeta potential, and a narrower size distribution. Following nanoparticle synthesis under varied pH conditions, their efficacy in methylene blue (MB) adsorption was investigated. Notably, nanoparticles synthesized at pH 11 demonstrated the highest adsorption capacity, registering maximum MB adsorption capacities of 188.68 mg/g, while pH 10 and 12 counterparts exhibited capacities of 169.49 mg/g and 175.44 mg/g, respectively. The adsorption processes conformed to the Langmuir–Freundlich isotherm model, with the pseudo-second-order model offering superior fitting to elucidate MB adsorption kinetics, thereby indicating the involvement of chemical adsorption mechanisms. It was discerned that MB adsorption encompassed both physical and chemical mechanisms, encompassing electrostatic attraction between the negatively charged surface of the nanoparticles and the cationic dye, as well as electron exchange interactions between MB and the functional groups present on the adsorbent surface. Thermodynamically speaking, this adsorption process exhibited an exothermic nature, with a preference for ambient temperatures. Magnetic separation post-adsorption was conveniently executed, and all nanoparticles demonstrated potential for reuse for a minimum of five cycles. Moreover, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed to assess and select the most favorable alternative from the available options. Based on the evaluation of 27 distinct criteria, it was determined that Fe3O4 synthesized in an environment with pH 11 emerged as the optimal choice, aligning with the initial findings from the adsorption assessments.

A novel fuzzy TOPSIS method based on T-spherical fuzzy Aczel–Alsina power Heronian mean operators with applications in pharmaceutical enterprises’ selection

One of the most significant and complete approaches to accommodate greater uncertainty than current fuzzy structures is the T-Spherical Fuzzy Set (TSPFS). The primary benefit of TSPFS is that current fuzzy structures are special cases of it. Firstly, some novel TSPF power Heronian mean (TSPFPHM) operators are initiated based on Aczel–Alsina operational laws. These aggregation operators (AOs) have the capacity to eliminate the impact of uncomfortable data and can simultaneously consider the relationships between any two input arguments. Secondly, some elementary properties and core cases with respect to parameters are investigated and found that some of the existing AOs are special cases of the newly initiated aggregation operators. Thirdly, based on these AOs and Aczel–Alsina operational laws a newly advanced technique for order of preference by similarity to ideal solution (TOPSIS)-based method for dealing with multi-attribute group decision-making (MAGDM) problems in a T-Spherical fuzzy framework is established, where the weights of both the decision makers (DMs) and the criteria are completely unknowable. Finally, an illustrative example is provided to evaluate and choose the pharmaceutical firms with the capacity for high-quality, sustainable development in the TSPF environment to demonstrate the usefulness and efficacy. After that, the comparison analysis with other techniques is utilized to demonstrate the coherence and superiority of the recommended approach.

Decision-Making System for Selecting Alternative Product Purchase Stores in Tokopedia Using A Combination of SAW and TOPSIS

In the era of advancing digital technology enabling online business transactions, e-commerce platforms like Tokopedia have rapidly grown in Indonesia, providing consumers with a wide array of products and services. However, this abundance of choices often leads to consumer confusion when selecting alternative stores for their purchases. Additionally, Tokopedia's search filter feature is limited, merely sorting products based on selected criteria without considering the consumer's specific needs. To address these issues, a decision-making system is essential, aiding consumers in choosing products from alternative stores that best align with their individual preferences and predetermined criteria. This study proposes a combined methodology employing the Simple Additive Weighting (SAW) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Initially, the SAW method normalizes values (r), which are subsequently ranked using the TOPSIS method to generate recommendations for alternative stores based on input criteria and weights. The adoption of this decision-making system is poised to enhance the online shopping experience for Tokopedia users by providing well-informed recommendations, improving overall satisfaction, and streamlining the purchasing process. In conclusion, this research offers a promising approach to addressing the challenges posed by the abundance of choices in online retail, ultimately benefiting both consumers and online businesses.

Economic Evaluation Method of Modern Power Transmission System Based on Improved Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Best-Worst Method-Anti-Entropy Weight

As the demand for power supply increases, the investment in the power transmission system constantly increases. An accurate economic evaluation of the power transmission system is essential for future investment decisions and management. Applying a single method in economic evaluation leads to excessive subjective consciousness and unreasonable weight allocation. The Euclidean distance in the traditional TOPSIS method only partially works on the condition that the criteria are linearly correlated. To solve these problems, an economic evaluation method based on improved TOPSIS and BWM-anti-entropy weight is proposed. For the assignment of weights, the method retains the advantages of subjective and objective weighting methods based on the Nash equilibrium, breaks through the limitation of utilizing a single method, which contributes to one-sided results, and enhances the scientific rigor and rationality of the comprehensive weighting process. Furthermore, based on comprehensive weights, the method improves the TOPSIS by introducing the Mahalanobis distance and Pearson correlation coefficients, which can eliminate the influence of linear correlation. Finally, ten 500 kV transmission and transformation projects are analyzed and ranked to verify the method’s feasibility. Empirical analysis shows that the method can effectively evaluate the economic benefits of the power transmission system.