Global Sensitivity Analysis for Carbon Storage Site Ranking and Selection

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.

Application of AHP, TOPSIS, and TFNs to plant selection for phytoremediation of petroleum-contaminated soils in shale gas and oil fields

Dam site selection is an important task in water resource management and it depends on a number of biophysical as well as socio-economic factors. Dam site selection is becoming important research area due to the increase of water scarcity and also to prevent flood in certain area. This paper presents Multi Criteria Decision Making (MCDM) approach in water resources management through the integration of Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). These methods were applied for identification of suitable dam site in Tlawng sub-basin. The influential criteria for dam site selection were initially identified through literature review and experts opinion which was followed by the selection of four (4) feasible sites after having studied Tlawng watershed. Lastly, AHP and TOPSIS were applied to determine the relative weight and rank respectively.

Penelitian ini bertujuan untuk merancang dan mengimplementasikan Executive Support System (ESS) yang efektif menggunakan metode Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP), dan Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) dalam konteks perencanaan strategis. Kemampuan ESS dalam mendukung pengambilan keputusan eksekutif dihadapkan pada kompleksitas faktor dan kriteria yang melibatkan banyak aspek bisnis. Metode SAW digunakan untuk memberikan nilai relatif pada setiap kriteria, memberikan pendekatan yang sederhana dan mudah dimengerti. AHP digunakan untuk menangani penilaian kriteria secara hierarkis, memungkinkan penetapan bobot yang lebih akurat berdasarkan tingkat hierarki kriteria. TOPSIS digunakan untuk memilih alternatif terbaik dengan mempertimbangkan kedekatan dengan solusi ideal. Penelitian ini adalah penelitian kuantitatif dengan menggunakan metode kepustaakaan. Hasil penelitian menunjukkan bahwa integrasi metode SAW, AHP, dan TOPSIS dalam ESS memberikan kontribusi positif dalam meningkatkan kemampuan sistem dalam memberikan dukungan yang lebih optimal bagi pengambilan keputusan eksekutif. Kesederhanaan SAW, penilaian hierarkis AHP, dan ketepatan pemilihan TOPSIS bekerja bersama untuk memberikan solusi yang akurat dan efisien.

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.

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.

Comparative and optimal study of energy, exergy, and exergoeconomic performance in supercritical CO2 recompression combined cycles with organic rankine, trans-critical CO2, and kalina cycle

On-site development of wave energy resources is a promising way to overcome power-shortage problems on islands. It is necessary to select suitable islands to deploy wave power plants, which are influenced by multiple factors related to resources, technology, economy, society, and environment. This study develops a two-stage decision framework to identify feasible islands and determine priority order based on geographic information systems (GIS) and multicriteria decision-making (MCDM). In the exclusion stage, unfeasible marine areas are excluded based on exclusion criteria and feasible island alternatives are identified. In the evaluation stage, alternatives are evaluated by evaluation criteria using the combined weighting method and the technique for order of preference by similarity to ideal solution (TOPSIS)-grey relation analysis (GRA) method. As the combined weighting method is based on the fuzzy group decision-making (GDM)-analytic hierarchy process (AHP) and the entropy method, it can effectively reduce subjective deviation. The proposed framework is applied in Shandong Province. It identifies 13 inhabited islands feasible for constructing wave power plants, among which Daguan, South Changshan, and Xiaoguan are the optimal ones. Sensitivity analysis is performed to verify the feasibility of the proposed framework. The results show that it is effective and could provide reference for practical engineering.

Technologies of renewable energy (RE) play a vital role in increasing economic growth in many countries and present a solution for many social, ecological, and political problems. Though, RE faces many barriers that prevent its development. So, these barriers are ranked and identified in this work, including five main barriers and fifteen sub barriers. In addition, five strategies are identified and ranked. The first step in this work, the Analytical Hierarchy Process (AHP) approach used to rank main and sub barriers under Single Valued Neutrosophic Sets (SVNSs). Then Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach assessed the five strategies. The outcomes of this work show that Commercial barriers ranked as the highest barriers and social-ecological ranked as the lowest barriers by using the AHP approach. Outcomes by neutrosophic TOPSIS show that capital assistant ranked as the highest strategies and RE goals ranked as the lowest strategies. This work can help decision-makers, governments for building a RE by using these strategies to overcome barriers that faced them.

Determining outstanding students at Baturaja University is an important process that requires fair and objective assessment based on relevant criteria. The purpose of this study is to develop a Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to assist the university team in the process of selecting outstanding students. This study took a sample of 50 students who had a Cumulative Grade Point Average (GPA) ≥ 3.5 and a track record of non-academic achievements. The four main criteria used in the assessment are Academic, Non-Academic, Attendance, and Attitude and Ethics. AHP is used to determine the weight of each criterion, while TOPSIS is applied to obtain the final ranking of students based on their proximity to positive and negative ideal solutions. The expected results of this study are a DSS that is able to provide objective student ranking recommendations, reduce subjectivity in assessment, and assist the selection committee in making fairer and more consistent decisions. This DSS is expected to improve efficiency and accuracy in the process of selecting outstanding students at Baturaja University.

Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.

The changes of land surface characteristics due to urbanization lead to various environmental problems such as increasing the runoff which can lead to flooding and the poor quality of receiving waters. Among different land uses in urban areas, the industrial areas are highly environmentally degraded land areas which annually discharge high amounts of contaminated stormwater to natural waterways. However, industrial areas plays major role in a country’s economy and therefore it is important to identify optimum strategies to improve the quality of runoff in such areas. Green Infrastructure (GI) practices integrate measures to restore the green space in urban areas and are currently becoming one of the promising strategies around the world as source control measures of stormwater, especially when implemented as treatment trains. For a complex land use like an industrial area, the reality in optimizing GI treatment trains can incorporate several aspects related to environmental, economic and social objectives which are expected of GI through their implementation. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used in this study to identify compromise optimum treatment train configurations and the sizing combinations of GI treatment trains for a case study industrial area in Melbourne, Australia. Moreover, a sensitivity analysis was performed to validate the results obtained through TOPSIS by considering several weighting schemes for different performance measures. The results of the sensitivity analysis assessed the most sensitive performance measures for the weight changes. The methodology proposed in this study was successful in optimizing both the selection and sizing of a GI treatment train for an industrial area simultaneously.

Countries are now shifting from one-off lunar exploration missions to the establishment of a lunar base for long-term sustainable surveys. The selection of a suitable site plays a crucial role in sustaining the base’s operation and facilitating scientific research. Previous site selection methods have been limited in their ability to consider multiple objectives and factors simultaneously, often relying heavily on expert knowledge. To address this challenge, this paper proposes a comprehensive site selection method that integrates multiple engineering and scientific objectives/factors. Through site selection factor comprehending, gridded data processing and site evaluation based on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the proposed method balances subjective and objective considerations and outputs quantitative descriptions of the most suitable candidate sites. This paper applies the proposed method to the range of 75°S − 90°S. The results reveal four large areas with continuous high suitability near the South Pole, while a small area located at the rim of Cabeus B crater shows the highest suitability. Qualitative and quantitative comparisons are conducted between the areas selected by the proposed method, areas recommended by previous studies, and areas announced by Artemis III. The candidate areas identified in this paper outperform others in terms of a wider range of site selection factors, making them valuable references for future lunar base site determination. Additionally, the proposed site selection method holds relevance for similar site selection tasks where multiple objectives are set. It offers a more automated and quantifiable approach, minimizing manual intervention and providing robust results for decision-making processes.