Watershed prioritization using morphometric analysis by MCDM approaches

The importance of disaster logistics and its share in the logistics sector are increasing significantly. Most disasters are difficult to predict; therefore, a set of measures seems to be necessary to reduce the risks. Thus, disaster logistics needs to be designed with the pre-disaster and post-disaster measures. These disasters are experienced intensely in Turkey and the importance of these measures becomes more evidential. Therefore, accurate models are required to develop an effective disaster preparedness system. One of the most important decisions to increase the preparedness is to locate the centres for handling material inventory. In this context, this paper analyses the response phase designing the disaster distribution centres in Turkey at the provincial level. AHP (Analytical Hierarchy Process) based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and goal programming model integration is used to decide alternative locations of distribution centres. TOPSIS method is employed for ranking the locations, which is based on hazard scores, total area, population, and distance to centre. Two conflicting objectives are first proposed in the goal programming formulation, in which maximization of the TOPSIS scores and minimization of the number of distribution centres covering all demands named set covering model are included. Although Gecimli has the highest priority with 0.8 p score in the TOPSIS ranking, Altincevre (0.77) and Buzlupınar (0.75) ensure both the TOPSIS score and coverage of the demand nodes. The results from this paper confirm that the computational results ensure disaster prevention insights especially in regions with limited data.

This article describes in detail how optimizing performance studies were measured on the selection of low global warming potential (GWP) refrigerants for automobile air conditioning to obey the environmental protocols with the multi-criteria decision-making (MCDM) tools. Among 14 alternatives, three different types of MCDM tools are used in this study, i.e., the technique for order of preference by similarity to ideal solution (TOPSIS) approach, evaluation based on distance from average solution (EDAS), and multi-objective optimization based on ratio analysis (MOORA) for time consumption. For the data processing, the thermodynamic characteristics, environmental friendliness, and economic circumstances are optimized with the multiple response attributes, including the latent heat of vaporization, thermal conductivity, vapor pressure, saturated fluid density, specific heat capacity, dynamic viscosity, GWP, ozone depletion potential, and cost per pound. From MCDM techniques, the grade values and weights assigned by decision-makers are standardized into a comparable measure. Among the 14 refrigerants, R430A has been applied foremost in EDAS, TOPSIS, and MOORA methods with the highest closeness coefficient values of 0.786, 0.701, and 0.064, respectively. R-744 was found to be the worst refrigerant by both EDAS and TOPSIS methods, while R1233zd (E) was found to be the worst refrigerant by the MOORA method.

Highways are one of the main structures of cities in the field of economic, social, and environmental facilities that connect cities, regions, and people each other. Determining the suitable highway routes includes difficult and complex processes due to the construction costs. Additionally, priorities, expectations, and constraints for economic, social, and environmental parameters must be considered together to provide efficient solutions to requirements. Multi Criteria Decision Analysis (MCDA) techniques such as Analytical Hierarchy Process (AHP), Ideal Solution Similarity Selection Ranking Technique (TOPSIS), and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Least Cost Path Algorithm (LCPA) with Geographical Information Systems (GIS) combination are the most suitable way to overcome these complexities. In this study, slope, aspect, geology, elevation, distances to roads, settlements, water bodies, fault lines, buildings, natural disasters, protected sites, population, and land use were selected to determine most suitable highway construction areas and route. The AHP, TOPSIS, and VIKOR methods were applied to calculate cost surfaces for least cost paths generation with LCPA, and the generated three routes were compared. As a result of the comparisons VIKOR route was the most suitable route considering the topographical statistics and all the three methods consistent with each other and current road.

PurposeThe purpose of this study is to provide a decision support tool to deal with the problem of seting priorites among patients competing for limited health care resources. Limited resources and unlimited demands prevent health-care services to be provided to all those in need. This became publicity evident with the current Covid-19 pandemic. Although controversial, health care rationing has always existed and is now inevitable. Setting priorities becomes then inevitable. How to define those priorities is a complex and yet irresolvable issue mainly because it involves several and conflicting criteria, translated into efficiency and equity considerations. This is why multi-criteria decision analysis (MCDA) was introduced to health care as an appropriate decision-support framework for solving complex problems.Design/methodology/approachThis paper proposes the application of two combined approaches – analytic hierarchy process (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and AHP-VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), as decision support tools to rank patients with competing needs in a more effective and equitable way. A rationing scenario involving four patients, differentiated by personal characteristics and health conditions, is used to illustrate, test and compare the applicability of both approaches. After extraction of the relative weights of the prioritization criteria involved in the hypothetical scenario from paired wise comparison methods, TOPSIS and VIKOR priority setting methods were designed.FindingsResults suggest that patients ranking from both combination approaches are similar and in accordance with the order made directly by health-care professionals. Therefore, the relative weights computed by AHP in combination with TOPSIS and/or VIKOR methods could be used with suitable applicability by health-care decision-makers.Originality/valueThis study is the first attempt to apply a combination of MCDA methods to patients’ prioritization context and the first to cross previous studies to deepen and consolidate the research.

This study is designed to provide paediatric surgeons' perspectives on the relative importance of the criteria for choosing a surgical mode for undescended testicle treatment between open surgery (orchiopexy) or laparoscopic surgery and determine the suitable surgical mode by using the multicriteria decision‐making method. The analytic hierarchy process (AHP), the technique for order preference by similarity to ideal solution (TOPSIS), and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods are utilized. A decision hierarchy is set with a goal, criteria, and alternatives. Our model is developed on the basis of four main criteria (time‐related, patient‐related, recovery‐related, and complication‐related factors) and 11 subcriteria (operation duration, length of stay in hospital, preoperative preparation time, recovery period after surgery, age of patient, weight of patient, aesthetic appearance, quality of life satisfaction, recurrence, possibility of infection, and vital function) as well as two alternatives, laparoscopy and open surgery. An online questionnaire was sent to the paediatric surgeons; responses from the 31 experts (i.e., paediatric surgeons) indicate that the most important criteria are found to be the time‐related factors, especially preoperative preparation time. On the other hand, the least important criteria are found to be complication‐related factors. Moreover, laparoscopy is chosen as the most suitable method for the undescended testicle using the AHP, TOPSIS, and VIKOR methods. This study helps paediatric surgeons' decision making by elucidating their priority criteria and representing their decision‐making process in terms of quantity with the help of AHP, TOPSIS, and VIKOR methodologies.

The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are among the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision-making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. The geographical criteria are geology, land use, sediment, erosion, slope, groundwater, and discharge. The water quality criteria include Soluble Sodium Percentage, Total Dissolved Solid, Potential of Hydrogen, and Electrical Conductivity of water. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this study area. Actual locations of dams constructed in the area were used to verify the results of both methods.

To improve the user perception of design decisions for living spaces in rural tourism-based elderly housing scientifically, a design approach is proposed from the perspective of user needs. This approach establishes an innovative model for the design of living spaces in rural tourism-based elderly housing by integrating the Kano model, the Analytic Hierarchy Process (AHP), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Firstly, the KJ method is used to extract the raw user needs, and after data cleaning, the Kano model is applied to categorize the attributes of these initial needs. Subsequently, the AHP method is used to construct a hierarchical model of user needs, enabling the calculation of the weight values of needs across different levels. User needs with higher weight values are integrated to create the design, and three design schemes are proposed for comparative analysis. Finally, the TOPSIS method is used to comprehensively evaluate the three design schemes derived from the user needs items identified by the Kano model and AHP method, thereby validating the feasibility of each design scheme. Experimental results show that the user needs-driven living space, constructed using the Kano model, AHP method, and TOPSIS method, transforms subjective concepts into specific design parameters through both qualitative and quantitative methods. This approach not only effectively addresses user needs but also provides solid theoretical support for the design of living spaces in rural tourism-based elderly housing.

Evaluation of key nodes is a hot issue in social networks. Existing research primarily evaluates the importance of nodes in social networks based on centrality metrics, neglecting the node’s own attributes. After analyzing the topology attributes and the basic attributes of nodes, this article proposes a key nodes evaluation method for social networks, which is based on analytic hierarchy process (AHP) and improved Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), termed AE-VIKOR. Considering global attributes, local attributes, and positional attributes of nodes, three evaluation metrics are constructed. The subjective and objective weights are computed by AHP and entropy weight method, respectively. The comprehensive weights of metrics are determined by combination weighting method based on square sums of distance. Due to the excessive weight of specific metrics and excessive difference in data distribution, the computation of individual regret value depends too much on a single metric in VIKOR method, individual regret value is optimized by weighted sum of closeness between the scheme to be evaluated and the negative ideal scheme. Multimetric evaluation schemes are ranked to achieve the evaluation of key nodes. Experiments on two real social network datasets show that the key nodes evaluated by AE-VIKOR have stronger information spread ability and more fans than the ones of the existing methods. In addition, the validity of the three metrics and the two improvements on the VIKOR method are verified by ablation experiments.

<p>One common multi-criteria decision making (MCDM) technique is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is frequently applied in several application fields. Finding an ideal and an anti-ideal solution, which are then utilized to determine the distances between the alternatives and the ideal solution, is the foundation of the TOPSIS approach. The method then ranks the alternatives according to their closeness to the ideal solution. TOPSIS is able to handle both quantitative and qualitative criteria, however, the method can be sensitive to the weight of the criteria, and the ranking results can be influenced by the choice of the reference alternatives. This paper provides an overview of the TOPSIS method, its applications, main characteristics and limitations. The paper also provides step-by-step instructions on how to apply the TOPSIS method, including the determination of the criteria weights, the construction of the decision matrix, and the calculation of the TOPSIS scores.</p>

The multi-criteria decision-making (MCDM) method often entails a number of steps, such as identifying the decision problem, defining the criteria, calculating the weighting of the criteria, assessing the alternatives against the criteria, and finally choosing the best alternative based on the overall evaluation. In this paper, the essential factor for sports, politics, journalism or media, and technological empowerment of women in India are found by MCDM techniques, which may also be utilized to examine the key factors influencing women’s empowerment. The uses the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM methodologies are taken to discover the optimal criteria for empowerment. The decision-making for finding the factors is done by taking multi experts’ opinions. First, determined the best criteria among the six criterion’s, such as Family Support (C1), Financial Support (C2), Cultural and Religious Barrier (C3), Child Marriage (C4), Nutrition (C5), and Shame and concealment (C6). The weights are calculated by the AHP method. According to the importance of the criteria, select a significant alternative for empowering women in many fields. Also take six possibilities into consideration, which are Empowerment in Sports (A1), Empowerment in Politics (A2), Empowerment in Administrative Service (A3), Empowerment of Journalism or Media (A4), Empowerment for Social Work (A5) and Empowerment of Technological (A6) and they are ranked by TOPSIS method. To verify the validity and robustness of our result, sensitivity analysis is performed by removing some criteria to make sure the procedure is reliable and a comparative study using a fuzzy environment.

The TOPSIS method in the Decision Support System for Determining Outstanding Students at SMP XX explains that this method is used to select alternatives (students) who have the closest distance to the positive ideal solution and the furthest from the negative ideal solution. This method considers criteria such as academic grades, activeness in extracurricular activities, and disciplinary attitudes. By implementing TOPSIS, it is hoped that objective and accurate decisions can be made in determining outstanding students. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method was chosen because of its reliability in overcoming complexity and uncertainty in multi-criteria decision making. Eka got a preference value of 0.31144246, Elsa got a preference value of 0.62095919, Frits got a preference value of 0.80287008, and Ninik got a preference value of 0.38000306. With the results of these preference values, it can be determined that Frits gets rank 1, Elsa gets rank 2, Ninik gets rank 3, and Eka gets rank 4.

Today there are various corporate sustainability indexes which are indicators of company performance. However, establishing exactly corporate sustainability indicators for all companies is quite difficult. Because corporate sustainability includes not only internal factors but also external factors (for example environmental factors) that affect company performance. In this study; firstly, sustainability, corporate sustainability and dimensions of corporate sustainability concepts will be explained, then corporate sustainability performance of an international company (X Company) will be evaluated. Data were acquired from the company’s annual reports. Indexes, which used in previous studies on this topic, were based; thus corporate sustainability indicators have been established. In the study, the company’s corporate sustainability performance will be analyzed with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) Method that is a multi-criteria decision making (MCDM) method. In this study, the objective has been reached and accurate results were obtained because of mathematical methods for the assessment of corporate sustainability performance. Corporate sustainability performance with more indicators can be analyzed in the future studies. Also; other methods (for example; AHP, ELECTRE Method or Fuzzy Set Theory), which are instead of Entropy and TOPSIS methods, will be used in the future studies.

This study presents a comprehensive multi-criteria decision-making (MCDM) framework for evaluating and selecting optimal non-destructive testing (NDT) techniques for oil and gas facility maintenance operations. This research used a Fuzzy Analytic Hierarchy Process (FAHP) integrated with multiple MCDM methods to assess eight NDT techniques including radiographic testing, ultrasonic testing, and thermographic testing. The evaluation framework incorporated seven technical criteria and seven economic criteria. The FAHP results revealed spatial resolution (0.175) as the most critical technical criterion, followed by depth penetration (0.155) and defect characterization (0.143). For economic criteria, downtime costs (0.210) and operational costs (0.190) emerged as the most significant factors. This study used TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment of Evaluations), and VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) methods to rank NDT techniques, with results consolidated using the CRITIC (CRiteria Importance Through Intercriteria Correlation) method. The final techno-economic analysis identified radiographic testing as the most suitable NDT method with a score of 0.665, followed by acoustic emission testing at 0.537. Visual testing ranked lowest with a score of 0.214. This research demonstrates the effectiveness of combining fuzzy logic with multiple MCDM approaches for NDT method selection in offshore welding operations.

Cost-Effectiveness Analysis of Surgical Approaches Total HIP Arthroplasty

PurposeThe purpose of this paper is to propose a novel integrated approach using analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods for evaluation and prioritization of appropriate manufacturing flexibility type required in the face of multiple environmental uncertainties.Design/methodology/approachUsing a case study of an Indian fashion apparel firm, the study demonstrates the application of the proposed integrated framework for evaluation and prioritization of manufacturing flexibility. The study uses AHP method to determine importance weight of environmental uncertainty criteria and subcriteria and then employs TOPSIS method to determine the final ranking of manufacturing flexibility types required to cope up with these uncertainties.FindingsThe findings of the case suggest that the proposed integrated approach is feasible and practically implementable for manufacturing flexibility assessment.Research limitations/implicationsAHP has been extensively studied and used, but the major limitation of this proposed approach is the involvement of large number of pairwise comparisons leading to difficulty in maintaining consistency in pairwise comparisons.Practical implicationsThe proposed approach can work as a benchmarking tool to practitioners in evaluating and prioritizing manufacturing flexibility alternatives and to suggest strategic allocation of resource by prioritizing different manufacturing flexibilities types.Originality/valueUnlike conventional approaches, the study provides meaningful knowledge to decision makers by demonstrating a simple, flexible, and efficient method to evaluate and rank the appropriate manufacturing flexibility types.