Lean manufacturing in the manufacturing sector corresponds to lean management in the service sector. When health services are considered, it is seen that the concepts that are important in the manufacturing sector have the same importance for health services. Because waste is the main problem of every sector. Lean management approach in the health sector enables improvements by developing solutions to many other problems of healthcare professionals, patients and hospitals, such as reducing transaction costs, ensuring patient safety, and reducing processing times. This study was carried out with the aim of establishing a lean health system by selecting the most appropriate lean management methodology in order to identify and prevent waste in health processes and to increase efficiency and service quality. In the study, the evaluation of lean methodologies that can be applied to prevent waste in health services is considered as a multi-criteria decision-making problem and a model has been proposed. In the proposed model, wastes were determined as research criteria and lean methodologies were determined as research alternatives. The solution phase of the problem was carried out in two stages with multi-criteria decision-making techniques. In the solution phase, the importance weights of 24 decision criteria were calculated with the SWARA method, while 5 alternatives were evaluated based on the decision criteria with the WASPAS method and the most suitable alternative was selected.

Layout design and selection often have notable effects on the performance of the manufacturing industry. This research investigates the Multi-Criteria Decision Making (MCDM) approach to find out the optimum plant layout design. The proposed methodology is demonstrated through the real-life setting for the gearbox manufacturing industry. Manual and computerized layout generation approach is used efficiently and accordingly, six layout designs are generated. The approach takes into account qualitative as well as quantitative performance criteria for the selection of layout design. Analytical Hierarchy Process (AHP) is applied to obtain the weight of qualitative measures. Ranking of alternatives is obtained through the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum-Product Assessment (WASPAS) both integrated with the Entropy method. Empirical findings indicate that the rank acquired using the TOPSIS method is perfectly parallel to those acquired through the WASPAS method, which confirms the applicability and potential of these methods. Also, the effect of the parameter λ in WASPAS method on performance score is stable. At the same time, this paper analyses the rank reversal phenomenon and proves that the ranking proposed by TOPSIS satisfies ranking stability.

It is a fact accepted by everybody that football is the most popular sport around the world. The result of a derby match may be very important for millions of people. Even the time seems to stop on a match day for so many people. Show and entertainment are the most important aspects of football. If soccer players have a high performance, a match may provide pleasure and excitement to audiences. Briefly, the performance and quality of soccer players are the key factors, which draw audiences. Goalkeepers are also one of the important components of football like other players playing different positions such as strikers, mid-fielders, and defenders. Moreover, a goalkeeper can affect the result of a match positively or negatively. Therefore, with the help of a mathematical approach as the methodological framework, it can be seen that the examination of the performance of goalkeepers can be beneficial for decision-makers performing in the fields of sport and the future studies. The current paper proposes an improved integrated multi-criteria decision-making approach to evaluate the selection of goalkeepers; and this model can be applied for goalkeeper’s performance analysis. The proposed model combines the weights of criteria calculated with the help of both the CRITIC and the PSI techniques by applying the weight aggregation operator. It also ranks the decision alternatives by implementing the WASPAS technique based on the final criteria weights obtained by using the weight aggregation operator. In addition, a comprehensive sensitivity analysis consisting of three stages was performed to verify the validation of the suggested hybrid model. It has been observed that A11 has remained the best option for all scenarios. As a result, the results of the sensitivity analysis prove that the proposed hybrid MCDM technique is a very useful, strong and applicable approach. Also, the results obtained by applying the proposed model are accurate, realistic, and reasonable according to the results of the validation test.

Conveyors and automated guided vehicles (AGVs) are important mechanical handling equipment used to transport loads from one place to another. Selection of proper material handling equipment is an intricate process. In the present paper two material handling equipment selection problem was solved using various newly developed multi criteria decision making (MCDM) methods. First a conveyor selection problem with six conflicting criteria and four alternatives was solved using four MCDM methods, i.e. combinative distance based assessment (CODAS) method, evaluation based on distance from average solution (EDAS) method, weighted aggregated sum product assessment (WASPAS) method and multi-objective optimization on the basis of ratio analysis (MOORA) method. Second an automated guided vehicles selection problem with six conflicting criteria and eight alternatives was solved using CODAS, EDAS, WASPAS and MOORA methods. Spearman rank correlation coefficient was calculated between the ranks obtained by various methods. The ranks obtained by these methods were even compared with the ranks of other MCDM methods and it was found that the relatively new methods CODAS, EDAS and WASPAS were in good agree-ment with each other.

The growth in renewable energy study has resulted in the expansion of mini-grids projects across different communities in developing countries. However, there is a need to ensure that a suitable business model is selected during the provision of mini-grid services in developing countries. This study presents a framework for ranking mini-grid business models. The proposed framework is a multi-criteria multi-decision (MCMD) making tool. The framework combines Criteria Importance Through Inter-criteria Correlation (CRITIC), TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) and WASPAS (weighted aggregated sum product assessment) methods. An interval type-2 fuzzy sets (IT2FSs) is used to convert the responses from decision-makers into crisp values. The applicability of the proposed framework was tested using Nigeria as a case study. Four potential mini-grid (private, government, community-based and public-private) business models for the case study were ranked using twelve criteria. The average values for the subjective and objective weight methods showed that electricity traffic and energy demand were the least and the most important criteria, respectively, for selecting a mini-grid business model. The results obtained showed that the best mini-grid model was a private model using a TOPSIS framework. A WASPAS framework ranked the community-based business model as the best model. This study results showed mini-grid business models in developing countries should be either private or community-based business models.

In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.

The electricity generation policy is a strategic policy that drives development in a community. Energy policies are often analyzed with the aim of generating a reliable and affordable electricity for a community. There is a high probability of achieving this aim when energy policy is combined with a community social, technical, economic and environmental needs. This paper determines a hybrid renewable energy source (HRESs) for a rural community using technical, economic, and techno-economic criteria. The selection process combines Criteria Importance Through Inter-criteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a solution method. This approach applicability was tested using six HRESs under economic and technical criteria. Ten technical and nine economic criteria were simulated for the HRESs using HOMER. The results from the HOMER software show that A5(PV/wind/battery) and A6 (PV/battery) had a renewable fraction of 1. The results obtained from the CRITIC method showed that the most important technical and economic criteria were diesel generator and total fuel cost, respectively. From an economic perspective, the best HRES for the case study was A4 (diesel/batteries), while A3 (wind/diesel generator/batteries) was the best HRES from a technical and techno-economic perspectives.