A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

Developmental Performance Ranking of SAARC Nations: An Application of TOPSIS Method of Multi-Criteria Decision Making

To be developed, nations are trying to cope up with the fast-changing economy and technology of the world. But the development of a nation does not depend only on these two factors rather several other indicators are essential to a country’s development. The present study deals with the progress of the SAARC (South Asian Association for Regional Cooperation) countries towards development through social, economic and environmental stability. This study aims at analyzing the comparative developmental performance of the SAARC nations in accordance with the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). In this study, we have prioritized the 8 SAARC nations based on 4 indicators (economic, demographic, health and environment indicators) and 20 variables using the multi-criteria decision-making method (MCDM). The result showed that Sri Lanka has prioritized 1st followed by Bhutan. India has been ranked 4th and Afghanistan was least prioritized

Developmental Performance Ranking of SAARC Nations: An Application of TOPSIS Method of Multi-Criteria Decision Making

To be developed, nations are trying to cope up with the fast-changing economy and technology of the world. But the development of a nation does not depend only on these two factors rather several other indicators are essential to a country’s development. The present study deals with the progress of the SAARC (South Asian Association for Regional Cooperation) countries towards development through social, economic and environmental stability. This study aims at analyzing the comparative developmental performance of the SAARC nations in accordance with the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). In this study, we have prioritized the 8 SAARC nations based on 4 indicators (economic, demographic, health and environment indicators) and 20 variables using the multi-criteria decision-making method (MCDM). The result showed that Sri Lanka has prioritized 1st followed by Bhutan. India has been ranked 4th and Afghanistan was least prioritized

A multi-criteria decision framework for unstructured complex problem: a strategy for biofuel production

A Multi-Criteria Decision Analysis (MCDA) approach was designed and used to evaluate different Fast Pyrolysis Unit (FPU) sizes. The MCDA approach is implemented via two models: Excel worksheet and automated model via Logical Decision® software. The proposed MCDA approach is an integration of the Pugh Concept Selection Matrix, Weighting Sum Method (WSM), and sensitivity analysis using Logical Decision® software. The data for the problem was collected from ten Subject Matter Experts (SMEs) using Pugh Matrix. In addition, two other integrated MCDA approaches were used to solve the same problem. The first approach integrated the Pugh Matrix and WSM. The second approach integrated the Pugh Matrix and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The designed framework is presented to identify Biofuel Production Stakeholders (BPS), their perspectives, and their requirements. The small FPU was found to be the best alternative using the three approaches. Furthermore, all these approaches allowed ranking of different alternatives based on the five perspectives of manufacturing biofuel production units: economic, environmental, technical, legal, and social perspectives. These five perspectives rely on 18 requirements that were frequently mentioned in previous research. The use of each approach gave different insight about the problem which could help decision-makers to understand the problem better and discuss the alternatives in depth. Sensitivity analysis suggested that the medium FPU is the best alternative in specific conditions under the perspectives-level analysis. On the other hand, it was suggested that the large FPU is the best alternative under specific conditions at the requirements-level analysis. An interesting finding from this research is that from the environmental perspective the medium FPU is recommended as the best alternative instead of the small FPU. In addition, the TOPSIS analysis provided the theoretical positive and negative ideal solutions to help the decision makers gain a better perception of the optimal design of FPUs. Moreover, WSM was found to be the simplest MCDA tool to use. In contrast, TOPSIS was found to be a more complicated tool yet similar to WSM both could not examine result robustness. The proposed approach provided the result robustness limitations

Understanding location decisions of energy multinational enterprises within the European smart cities’ context: An integrated AHP and extended fuzzy linguistic TOPSIS method

Becoming a smart city is one of the top priorities in the urban agenda of many European cities. Among the various strategies in the transition path, local governments seek to bring innovation to their cities by encouraging multinational enterprises to deploy their green energy services and products in their municipalities. Knowing how to attract these enterprises implies that political leaders understand the multi-criteria decision problem that the energy sector enterprises face when deciding whether to expand to one city or another. To this end, the purpose of this study is to design a new manageable and controllable framework oriented to European cities’ public managers, based on the assessment of criteria and sub-criteria governing the strategic location decision made by these enterprises. A decision support framework is developed based on the AHP technique combined with an extended version of the hesitant fuzzy linguistic TOPSIS method. The main results indicate the higher relative importance of government policies, such as degree of transparency or bureaucracy level, as compared to market conditions or economic aspects of the city’s host country. These results can be great assets to current European leaders, they show the feasibility of the method and open up the possibility to replicate the proposed framework to other sectors or geographical areas.The authors acknowledge the support from the European Union “Horizon 2020 Research and Innovation Programme” under the grant agreements No 731297. Also, this research has been partially supported by the INVITE Research Project (TIN2016-80049-C2-1-R and TIN2016-80049-C2-2-R (AEI/FEDER, UE)), funded by the Spanish Ministry of Science and Information Technology.Peer ReviewedPostprint (published version

Simulation of TOPSIS calculation in Discrepancy-Tat Twam Asi evaluation model

This research’s main objective was to provide information related to the simulation of each calculation stage of the TOPSIS method used in the Discrepancy-Tat Twam Asi evaluation model. The TOPSIS method is used to find dominant indicators in the Discrepancy-Tat Twam Asi evaluation model that determines the effectiveness of blended learning in ICT Vocational Schools. This research used a quantitative approach. The questionnaires were used as a data collection tool in this study. Questionnaires were distributed to 20 respondents (teachers and students at several ICT Vocational Schools in Bali, Indonesia) for initial data needs and distributed to fourexperts to obtain data on the TOPSIS calculation effectiveness results. The analysis technique in this research was carried out by comparing the percentage of effectiveness test results with the standards. The results of this research showed that the simulation of TOPSIS method calculation in the Discrepancy-Tat Twam Asi evaluation model had run more effectively, as indicated by score was 93.13%. The simulation results showed the dominant indicator that determines the effectiveness of the blended learning implementation was I-2 (the existence of academic community support)

Path Selection using Fuzzy Weight Aggregated Sum Product Assessment

The search for safe evacuation routes is an important issue to save flood victims so they can reach the evacuation centre. This research is a simulation of searching for safe and fast travel evacuation route that have 24 alternative routes. Every road that will be transverse has a limit with certain criteria. Calculate of the weight of the constraints using the Multi-Criteria Decision Making (MCDM) method, namely the Analytical Hierarchy Process (AHP) andWeight Aggregated Sum Product Assessment (WASPAS) based on Fuzzy logic. The criteria of obstacle that qualitative for obscurity so that it makes sense fuzzy will provide supportive input for the MCDM problem. The Fuzzy AHP method is applied to calculate the weight of an application while the Fuzzy WASPAS (WASPAS-F)method is used to determine the safest alternative route. By using the Fuzzy AHP and WASPAS-F methods, a safe and fast pathway weights 0.66