RETRACTED: E-commerce logistics distribution mode in big-data context: A case analysis of JD.COM

Against the satellite heterogeneous network optimal selection problem, in this paper we propose a network selection algorithm based on the Analytic Hierarchy Process (AHP) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The algorithm considers the parameters that may affect the network selection like quality of business services, user preferences, network load, and so on. The use of AHP is to calculate the weights of various parameters, and TOPSIS is used to obtain the final access network ranking. The simulation results verify the correctness and validity of the algorithm.

Multi-attribute decision making (MADM) is a state-of-the-art, popular technique for dealing with real-world problems. An effective decision can be made for various real-world problems involving multiple attributes to decide a proper solution. Software testing and bug fixing are essential steps in the field of software engineering. Bug triaging is a real challenge in large-scale software development. Bug triaging is the process of allocating newly reported bugs to the best developer who meets the requirements for addressing them. In this paper, a software developer ranking model based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed for an effective bug triaging process. Developers are ranked based on various criteria using the TOPSIS model for effective bug triaging. Assigning newly reported bugs to the appropriate and available software developer is a complex decision-making process. It involves consideration of multiple criteria for discovering the optimal solution. In software engineering, bug triaging refers to the process of allocating appropriate developers to a newly reported bug. This paper presents criteria for finding suitable developers using multi-criteria decision-making (MCDM) techniques. The Analytic Hierarchy Process (AHP) method is used to determine the weights of the criteria, and the TOPSIS MCDM technique is used to rank the most appropriate developer.

A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) is established to identify potential hazards in time. First, a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors: corrosion, external interference, material/construction, natural disasters, and function and operation. Next, the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method. Then, the TOPSIS of a multi-attribute decision-making theory is studied. The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines. The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS. Finally, the weight and the closeness coefficient are combined to determine the risk level of pipelines. Empirical research using a long-distance pipeline as an example is conducted, and adjustment factors are used to verify the model. Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible. The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive, rational, and scientific evaluation results. It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines. The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.

This paper employs a Game Theory-based Weighting and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to comprehensively evaluate the development vitality of new quality productive forces in Beijing, Tianjin, and Hebei. By integrating the Analytic Hierarchy Process (AHP) and Entropy Method to determine weights, a scientific evaluation index system is constructed, incorporating both expert opinions and objective data. The evaluation results indicate that Beijing excels in technological innovation and efficiency, Tianjin performs well in green development, while Hebei requires enhancement in industrial transformation and upgrading. Encompassing multiple dimensions such as technological innovation, intellectual resources, green development, production efficiency, and industrial transformation and upgrading, the assessment further validates the effectiveness of the evaluation methodology through case study analysis. The Game Theory-based Weighting approach effectively combines subjective and objective weights, enhancing the scientific rigor and accuracy of the evaluation. The results provide a decision-making basis for optimizing industrial structures, promoting regional collaboration, advancing green and low-carbon development, and improving social well-being in the Beijing-Tianjin-Hebei region. In conclusion, the proposed Game Theory-based Weighting and TOPSIS evaluation model serves as a powerful tool for assessing the development vitality of new quality productive forces in Beijing, Tianjin, and Hebei. It holds significant implications for driving regional high-quality development, achieving economic growth with high quality, and fostering sustainable social development.

The premise of the large-scale operation of electric buses corresponds to efficient charging service guarantees. Recent research on charging stations mainly aims to obtain the construction location and construction sequence through optimization methods or decision-making methods. This research has considered the aspects of geography, charging efficiency, economic efficiency, and emergency response capacity. The increase of charging stations will lead to competition among charging stations, unbalanced use of charging facilities, and unnecessary loss of electricity to the power grid. In fact, few studies pay attention to the actual operation of existing charging stations. Therefore, it is necessary to establish a scientific, comprehensive, and efficient charging services evaluation framework to support the actual operation of charging stations. Based on the analytic hierarchy process (AHP), this paper designs a multi-level indicator evaluation framework, which includes 6 first-level indicators and 20 s-level indicators. The first-level indicators are cutting peak and filling valley (A1), location and scale (A2), intelligent technology (A3), equipment efficiency (A4), operating income (A5), and reliability (A6). Through the questionnaire survey of ten experts in related fields, we understood the importance and attention of these indicators. The results show that the weights of indicators of location and scale index (A2) and reliability (A6) are high, which are 0.2875 and 0.2957, respectively. The least concerned indicator is equipment utilization efficiency (A4), at a weight of 0.0531. According to the actual data of charging stations in Zhengzhou, China, the comprehensive competitiveness of several charging stations is evaluated by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The result shows that station 1 has the highest comprehensive competitiveness, followed by station 2 and station 7. The evaluation framework proposed in this paper comprehensively considers a variety of factors. The combination of AHP and TOPSIS can reduce the uncertainty in experts’ evaluation of the service of the charging station.

Ecological agriculture projects have achieved a growing development in the context of low carbon. However, because of the great difference in these issues from traditional types, there exist risks in progression quality and sustainability. To better identify the risk, this paper proposes a novel hybrid approach that integrates the analytic hierarchy process (AHP) with technique for order preference by similarity to an ideal solution (TOPSIS), as well as an improved support vector machine (SVM) based on the brainstorming algorithm (BSO). First, a risk evaluation index framework is developed and elaborated in terms of the natural environment, society, market economy, management, technology, and finance. Then the traditional assessment can be derived from AHP with TOPSIS. In addition, BSO is applied to improve SVM for rapid computation. Finally, a case study is implemented to verify the accuracy of the proposed technique. In this research, based on the low-carbon perspective, artificial intelligence algorithm and risk assessment are introduced into the field of ecological agriculture project management, which is conducive to the rapid and effective evaluation of ecological agriculture project risk. It can improve managers’ risk awareness and risk management ability, reduce investment blindness, and help ecological agriculture projects achieve healthy and sustainable development under the background of low carbon, thus contributing to the development of a low-carbon economy.

Surface coal mines, when abandoned or closed, pose significant environmental and socioeconomic challenges. Repurposing these sites is crucial for sustainable land use and responsible resource management. This study presents a comprehensive decision framework tailored to the Indian mining context, utilizing a hybrid approach combining the analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) methodology. The proposed framework assesses and ranks alternative repurposing options by considering a multi-criteria evaluation, including ecological, economic, social, and regulatory factors. AHP is employed to determine the relative importance of these criteria, reflecting the unique priorities and perspectives of stakeholders involved in the repurposing process. TOPSIS then identifies the optimal alternatives based on their overall performance against the established criteria. This hybrid methodology contributes to informed decision-making in the sustainable repurposing of abandoned surface coal mines in India. It aids in identifying the most viable and environmentally responsible alternatives, promoting efficient land use and resource conservation while addressing the challenges associated with abandoned mine sites. The methodology’s applicability extends globally to industries facing similar repurposing challenges, facilitating the transition toward a more sustainable and responsible land reclamation and resource management approach. The methodology is implemented using real mine data and demonstrates the analysis for evaluation among multiple alternatives such as solar parks, fish farming, eco-resorts, forestry, and museums. In our study, eco-resorts show more promise based on the significant potential for local economic development, provision of local employment, long-term revenue generation, potential for upskilling local youth in management, gardening, construction, and animal husbandry, and serving as a site for exhibitions of various arts and crafts.

In the construction of a new power system, the identification and evaluation of power consumption status of power customers will become an important basis for them to participate in the emerging businesses such as demand response and virtual power plants. In order to ensure the power safety of important power customers, a new evaluation of power consumption status of important power customers based on the AHP (analytic hierarchy process)‐TOPSIS (technique for order preference by similarity to an ideal solution) algorithm is proposed by fully mining and applying the power big data. Firstly, a power consumption big data analysis platform based on the Hadoop architecture is built to provide a high‐performance platform support for big data analysis. Secondly, nine evaluation indexes are constructed from the three dimensions of voltage, load and synthesis, which objectively and scientifically describes the power consumption status of important power customers. Finally, the AHP‐TOPSIS algorithm is used to evaluate and analyse the voltage, load and comprehensive indicators respectively, thus, obtaining the evaluation values of three kinds of indicators. The power consumption status scores of important power customers are determined by the variable weight weighted summation. The rationality and feasibility of the method and algorithm are proved by example analysis and field verification. This method helps to promote the transformation from post fault emergency repair to warning beforehand. It has the multiple effects of ensuring safe power consumption, supporting accurate patrolling and active emergency repair serving.

Sustainable desalination process selection: Decision support framework under hybrid information

The demarcation of basic farmland scientifically is important to cultivated land protection, agriculture-economy development, and regional sustainable development. This paper took Fogang County as an example, calculated the amount of basic farmland protection and exclusion and then quantified the addition amount; established the evaluation system of farmland; used Analytic Hierarchy Process (AHP) and entropy method to determine the index weights; prioritized the selected cultivated land using GIS and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS); and then combined with the addition amount to optimize the basic farmland spatially. The study result proved that the demarcate method of basic farmland was feasible, and can provide scientific and technological support for basic farmland planning.

The safety issue during bridge construction and operation has become a major concern for the society. This research focuses on how to conduct integral health-status assessment for bridges in operation on the basis of test and monitoring data. The result of the assessment will be the foundation of bridge maintenance, damage repair and reinforcement decision-making. Bridge state assessment origins in America, where bridge management systems were developed to give comprehensive assessment and help make daily management and maintenance decision for medium and small bridges. Afterward, different bridge health-status evaluation methods have been developed. For small and medium bridges, bridge assessment is usually conducted by applying assessment code. For complicated bridge, such code could not reflect the complexity of the structure. Another assessment method is reliability method. Reliability method is based on theory of probability and fully considers the uncertainty of structures. Analytic Hierarchy Process (AHP) is proposed in the 1970s to conduct multi-criteria decision-making combining qualitative and quantitative factors. (Saaty 2008) Bridge state assessment is a typical multicriteria decision-making problem. In the assessment model, multiple assessment indexes should be taken into consideration, including quantitative indexes and qualitative indexes. When the AHP assessment model is built and the weight of each index is derived, the evaluation value of the base indexes of the model should be derived and then be integrated by a certain relationship to get an integrated evaluation value representing the general state of the bridge. This research focuses on the evaluation value of base level indexes and the integrated evaluation method. The base level indexes of the bridge health-status assessment model are all from field test and monitoring directly. They need to be transformed to unified non-dimensional evaluation value. Considering the fuzziness and uncertainty of the evaluation process and transformation process, fuzzy grading is used to give a quantitative description of the base index’s evaluation. Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is a multiple attribute decision making method, which was developed for ranking and evaluation of limited number of alternatives (Yoon & Hwang 1995). Under AHP assessment framework, an improved fuzzy TOPSIS method has been proposed to conduct overall assessment of bridges. An integrated evaluation method is proposed by improving TOPSIS method and adapting it to bridge health-status assessment. The improvements include: ① absolutization of positive and negative ideal solution value; ② establishment of the virtual ideal solutions; ③ calculation of variable weight of base-level indexes considering the impact of the variation of the base-level indexes ④ fuzzy assessment based on level sets; ⑤ defuzzificaiton and standardization treatment of the assessment result. A case study applying the proposed fuzzy TOPSIS methodis introduced. This implementation verifies the feasibility and utility of the proposed method.

BackgroundBy analyzing 23 evaluation indicators included in 14 national basic public health service programs in a region of Hohhot City, Inner Mongolia Autonomous Region, China, the performance of basic public health services in the region in 2021 were analyzed to clarify the implementation and conduct of relevant programs. We also use this study as a basis to radiate the work of municipal basic public health services centered on the region and the outstanding problems reflected and to provide theoretical contents and suggestions that can be referred to for the same regions in central and western China as well as worldwide.MethodsUsing the TOPSIS method as the basis for the data analysis method, the evaluation indexes are ranked in terms of their proximity to the idealized target, and combined with the entropy value method, Technique for order preference by similarity to an ideal solution (TOPSIS) and rank-sum ratio (RSR) were used to rank 14 basic health care providers by grade. A comprehensive evaluation of the performance of basic public health services in a region of Hohhot City, Inner Mongolia Autonomous Region in 2021 was conducted through a joint model of entropy -weighted TOPSIS and RSR, making full use of the characteristics and advantages of the fuzzy joint, and conducting a comprehensive analysis from the perspective of the ratio weight and the method of graded calculation, making the study more distinguishable and measureable.ResultsIn this study, for the regional basic public health services, a total of 23 evaluation indicators of basic public health service projects were included, among which the top three indicators with the weight of the entropy value method indicators were found to include the rate of Chinese medicine health management for the elderly, the rate of health management for the elderly, and the BCG vaccination rate after the analysis of the weight of the indicators; After the entropy-weighted TOPSIS evaluation showed that the Ci values of the regions were found to be between 0.378 and 0.715 through the calculation of the positive and negative ideal values of each indicator; RSR staging method evaluation showed that three community health centers (X2, X10, X12) had excellent evaluations of basic public health services; The number of evaluations as poor and moderate are 2 (X3, X9) and 9 (X1, X4, X5, X6, X7, X8, X11, X13, X14), respectively; Finally, the results of the entropy-weighted TOPSIS method and the fuzzy joint model of RSR staging method are basically consistent with the overall trend of the above two methods, and the reliability and credibility of the research results are high.ConclusionThe entropy-weighted TOPSIS and RSR joint model can evaluate the effectiveness of basic public health services in a more comprehensive and holistic way. The results of the RSR staging results and the related weight ratio analysis show that the basic public health service programs in Hohhot, Inner Mongolia Autonomous Region are relatively balanced, but there are some differences; The same genus of elderly Chinese medicine health management rate, health management rate of the elderly, BCG vaccination rate several indicators accounted for a higher weight, its correlation with the key population-related items is high, suggesting that the future key population health service items should be focused on, and future research should be suggested from two key research.

The Original TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) Method is a ranking method based on the principle that the chosen alternative should be as close to the ideal solution, rather than the negative-ideal solution, as possible. However, currently utilizing in establishing the evaluation system of indicator-based model, the Original TOPSIS Method is failed to take the weights of indices into account. Besides, other weighting method like Subjective Evaluation Method is proved to be largely influenced by various subjective situations. To resolve the problem of weighting, in this paper, we propose a new method named Modified TOPSIS Method utilizing Gray Correlation Analysis. By eliminating the mistakes caused by indices which are essentially measured by the same factors, it is useful to improve the evaluation system of indicator-based model. The verification utilizing Spearman's Rank Correlation Coefficient demonstrates that our Modified TOPSIS Method is improved.

Background: To basically solve the critical environmental problems, macro and infrastructural perspectives of rational development should be designed following environmental protection rules. Creating the proper performance measurement systems in every organization has had a promising interest in university studies, and many researchers are working on it. Methods: This research intends to compare and rank 4 evaluation performance models used in gas refineries. To achieve the desired model in this study, we employed the grounded theory. The study research consisted of 20 professionals and Health, Safety, and Environmental (HSE) managers of gas refineries who had relevant experience and skills in this area. The normal score was estimated based on the weight obtained from the Analytic Hierarchy Process (AHP) to apply the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) process and prioritize the models. Results: The pairwise comparison matrix of 4 research models of the balanced scoring card, European foundation for quality management business excellence model, Iran national quality award, and environmental performance evaluation depicted that the geometric mean of the evaluation criteria includes the following items: the capability to quantify qualitative data for environmental performance, facilitating, efficient implementing, structuring, and mapping a roadmap of organization maturity to select an environmental performance estimated at 1.22, 0.90, 0.95, and 0.96, respectively. Also, the normal weights of these four criteria are estimated at 0.3039423, 0.2242449, 0.2347026, and 0.2371102, respectively. Conclusion: The findings resulting from prioritizing the organization’s Environmental Performance Evaluation (EPE) models based on TOPSIS depicted that the suggested model with relative proximity to 99% is the first choice of EPE for the gas refinery.

Every year, some social assistance is distributed by the Ministry of Social Affairs to each village/Nagari aimed at low-income families. The problem of poverty data almost occurs in all village/Nagari governments. In Koto Baru Simalanggang, several issues arose, including social assistance being mistargeted, poverty assessment being very complex, no system helped in DTKS, and no empowerment/system was carried out in reducing social problems; thus, all were put into DTKS without being able to see the details. Thus far, for the examination of the data of the proposer of assistance, the Nagari government still uses manual methods; therefore, it takes a long time and is subjective to the settlement of low-income families. Posdaya Bundo Saiyo is assisting in Koto Baru Simalanggang for the poor beneficiaries. There needs to be a decision support system to determine people with low incomes in this Nagari; using the method to determine people with low incomes is more objective. The results of this study are in the form of a decision support system for the determination of people with low incomes, which is used as a reference for the Bundo Saiyo Posdaya to make recommendations for the determination of people with low incomes to the Mayor of Koto Baru Simalanggang using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytical Hierarchy Process (AHP) methods. Based on the comparisons made in this research, the AHP and TOPSIS methods have the same ranking results