A Clustering and TOPSIS-Based Developer Ranking Model for Decision-Making in Software Bug Triaging

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.

During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The GRA(grey relational analysis)-based TOPSIS(technique for order preference by similarity to an ideal solution) decision-making approach, in combination with the advantages of both GRA and TOPSIS, was developed to solve multiple criteria decision making(MCDM) in fuzzy environment where attributes weights and ratings were expressed in interval numbers. A numerical example is proposed to illustrate an application of the proposed model. Finally, the direction for further research was pointed out.

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.

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.

A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design

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.

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.

AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles

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.

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.

Extreme analysis of typhoons disaster in mainland China with insurance management

The process of bridges seismic retrofitting in the highway network is extremely costly and time consuming. In addition, the constraint on resources prevents the retrofitting of all the bridges at the same time. Besides, the bridges must be prioritized with simultaneous consideration of multiple criteria, including technical and socioeconomic aspect. This study intends to identify the major criteria and consider them simultaneously for prioritization of highway bridges additionally provides an effective technique for weighing these criteria. In this research, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method as a Multi-Criteria Decision-Making (MCDM) model is applied. TOPSIS method enables decision makers to deal with problems involving a large number of alternatives (bridges) and criteria. This methodology reduces multiple alternative (bridge) performances into a single value (ranking score) to facilitate the decision-making process for determination of the most suitable bridges for retrofitting. Suggested criteria include structural vulnerability, seismic hazard, anticipated service life, average daily traffic, interface with other lifelines, alternative routes and bridge importance. Moreover, relative importance (weight) of the criteria is assigned using Analytic Hierarchy Process (AHP) technique. The proposed method is applied to a real case of the Isfahan highway network.

A hybrid neuro-fuzzy analytical approach to mode choice of global logistics management

Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education