Performance Evaluation in Aggregate Production Planning Using Integrated RED-SWARA Method under Uncertain Condition

Robust nuclear power plant site selection using SWARA, MABAC, and SMART: A GIS-Based study on the Muria Peninsula

Industry 4.0 has the potential of growing industrialization and, on the other hand, disrupting the sustainability of prevailing manufacturing supply chains through inducing great challenges such as higher resource consumption that, in turn, results in global warming and climate change. As a result, researchers working in the area of sustainable supply chain 4.0 need to make deep evaluations on the challenges arising for manufacturing supply chains contemplating the improvement of their sustainability levels and having a digital transformation toward Industry 4.0. To fill this gap, the current paper designs an innovative framework on the basis of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique and the Complex Proportional Assessment (COPRAS) approach to evaluate the challenges that may arise for supply chain 4.0 in the q-Rung Orthopair Fuzzy Sets (q-ROFSs) setting. The proposed method uses an extended SWARA process to determine the criteria importance degrees considering the experts’ preferences. The performance of the proposed method was assessed by conducting an empirical case study under the q-ROFSs condition. Further, a sensitivity analysis was executed to check whether the proposed method is stable enough to be relied on parameter values. Finally, the results obtained were compared to those of currently used methods to verify the obtained results’ reliability. As revealed by the comparative results, the framework proposed in this article was of higher consistency and strength compared to other prevailing approaches.

Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment.

ABSTRACT: This paper presents a multi-stage stochastic model to address an aggregate production planning problem. The proposed stochastic model includes two random variables, namely, random demand and random quality, where the production system generates a random amount of defectives. The main contribution of this paper is to extend the traditional deterministic production planning model to take into account the impact of uncertainty, which yields to the development of an integrated stochastic model that jointly optimizes production management decisions considering quality concerns under a certain service level. The performance of the proposed stochastic model is analyzed to draw relevant managerial insights regarding the effects of such a service level target. Also, a sensitivity analysis is conducted to study the effect of varying several costs and system uncertainty parameters to validate the cost-effectiveness of integrated stochastic modelling. The obtained results demonstrate that uncertainty has a significant influence on the decision variables and the total incurred cost, and it is not advisable to ignore the presence of the stochastic variables since they significantly modify the optimal decisions. Keywords: aggregate production planning, quality, random demand, stochastic programming, optimization

Climate change is the greatest threat to our planet and way of life. There is an immediate need of decarbonisation and a push for a smooth transition to a world with no net carbon emissions. To achieve sustainability, fast-moving consumer goods (FMCG) firms are increasing their efforts to reduce their carbon footprint across their supply chains. The firms and government undertake several initiatives towards achieving the zero carbon mission. Hence, there is a need to identify the prominent enablers that may enhance the decarbonisation in the FMCG sector and contribute towards a net-zero carbon economy. The current study has identified and assessed the enablers (6 main criteria, 19 sub-criteria), including green innovation, green supply chain, sustainable decision-making, organisation decisions and government control from environment, social and governance (ESG) perspective. Eco-friendly manufacturing techniques and eco-friendly goods may give businesses a competitive edge and sustainability. The six primary factors that can help to reduce decarbonisation are evaluated using the stepwise weight assessment ratio analysis (SWARA) technique. The criteria and sub-criteria are assessed by SWARA method. A total of 32 experts from the FMCG industry are undertaken to validate and assess the enablers. This study identified and evaluated the ESG-based decarbonisation enablers in FMCG. The study shows that green innovations are ranked first, followed by organisational decisions and government control. This is likely the first study to examine how the FMCG industry's enablers for decreasing carbon footprints connect. The study is helpful to the supply chain managers and the other decision makers to implement well-designed processes for creating new products and a supply chain from the point of purchase to the place of supply, all backed by advanced technology and the appropriate regulatory adjustments.

Supplier selection in food supply chains (FSCs) is not much explored due to the inherent difficulties, complexities and nature of food industry. Food security and quality are top row topics in today’s world health scenario. During sudden food crisis, it needs extra attention where producers, suppliers, and stakeholders play the most vital roles. This paper puts forward a two-phase sustainable multi-tier supplier selection model for FSC based on an integrated decision analysis under multi-criteria perspectives considering sustainability criteria, suppliers and sub-suppliers. In the first phase, the model estimates supplier selection criteria weights using a combined version of step-wise weight assessment ratio analysis (SWARA) and level based weight assessment (LBWA) in conjunction with D-numbers. In the second phase, Measurement of Alternatives and Ranking according to the COmpromise Solution (MARCOS)-D method is applied to obtain a ranking pre-order of different tier suppliers. Moreover, several sensitivity analyses are carried out in order to examine model reliability. To check application practicability, the proposed model is implemented in a case study of WineSol Corporation in Spain. The proposed model is expected to serve as a kickoff point for developing advanced decision-making models for effectually address multi-tier supplier selection problems under uncertain environment.

A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations

Prioritising food loss and waste mitigation strategies in the fruit and vegetable supply chain: A multi-criteria approach

This study aims to identify and prioritize the key factors influencing export performance among Turkish exporters, based on the resource-based view (RBV) and industrial organization theory (IO), categorizing the factors as internal and external, and employing the Stepwise Weight Assessment Ratio Analysis (SWARA). Twenty-five factors across Internal (IF) and External (EF) categories were evaluated through expert assessments. Results reveal that Internal Factors (58.0%) significantly dominate External Factors (42.0%), indicating that Turkish exporters possess substantial control over their export competitiveness. The top five critical factors are Management and Leadership (9.6%), Strategy (6.2%), Technological Change (5.3%), Industry and Sector Activity (5.0%), and Competitors (5.0%). Surprisingly, traditional factors such as firm size, international experience, and digitalization ranked much lower, challenging conventional assumptions about export success. A leave-one-out (LOO) sensitivity analysis further validated the robustness of these rankings, with Management and Leadership, and Strategy emerging as the most stable and dominant factors across all scenarios. The predominance of management and strategic factors over structural characteristics suggests that even smaller, less experienced companies can achieve export success through effective leadership and strategic planning. These findings contribute theoretically by supporting the notion that the resource-based view has a greater impact on export performance than the industrial organization theory, and they provide practical guidance for companies to focus on managerial and leadership skills, organizational capabilities, and strategic approaches to enhance export investments. The study presents the first comprehensive SWARA-based ranking of export performance factors in the Turkish context, providing empirical evidence to support the internal-external factor debate in the international business literature.

The achievement of countries in generating scientific publications is also a reflection of their efforts in the scientific domain. The quantitative volume of these publications is not a criterion alone, but the fact that they are a source of inspiration for other scientists carrying out their studies in other countries is an important indicator in terms of evaluating the quality of publications. Based on this emphasis on scientific publications, this research aimed to assess the performance of nineteen G20 countries upon scientific publication data issued by The SCImago Journal & Country Rank and covering the years 1996-2022. The evaluation criteria do not only consist of the number of scientific documents, but also number of citable documents, number of citations, number of self-citations, number of citations per document and H-index values. Fuzzy Step-wise Weight Assessment Ratio Analysis (Fuzzy SWARA) method is employed to determine the priorities of the criteria with the participation of ten researchers from different scientific disciplines. As an outcome of the application of this method, the order of importance of the criteria is determined as H-index, number of citable documents, number of citations per document, number of citations, number of documents and self-citation. The performance order of nineteen countries is performed by using the CODAS-LN method, which includes a logarithmic normalization version of the COmbinative Distance-based ASsessment (CODAS) method and is a very convenient approach in cases where the data is not normally distributed. The results revealed that the United States has a superior position in terms of scientific publication performance, while the United Kingdom, Germany, Canada and France are aligned in the top five order. The consistency of the applied method is also confirmed by two different sensitivity analyses.

In this article two multi-stage stochastic linear programming models are developed, one applying the stochastic programming solver integrated by Lingo 17.0 optimization software that utilizes an approximation using an identical conditional sampling and Latin-hyper-square techniques to reduce the sample variance, associating the probability distributions to normal distributions with defined mean and standard deviation; and a second proposed model with a discrete distribution with 3 values and their respective probabilities of occurrence. In both cases, a scenario tree is generated. The models developed are applied to an aggregate production plan (APP) for a furniture manufacturing company located in the state of Hidalgo, Mexico, which has important clients throughout the country. Production capacity and demand are defined as random variables of the model. The main purpose of this research is to determine a feasible solution to the aggregate production plan in a reasonable computational time. The developed models were compared and analyzed. Moreover, this work was complemented with a sensitivity analysis; varying the percentage of service level, also, varying the stochastic parameters (mean and standard deviation) to test how these variations impact in the solution and decision variables.

The green supply chain operations try to minimize environmental impact over the product's lifetime including product recycling or use, reduction of harmful substances, resource saving, green design, etc. Supplier selection is the vital issue in green purchasing. This paper aims to develop applicable and efficient methodology for green supplier selection. The proposed methodology includes the combination of Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA-F) and Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (MARCOS-F) methods. Fuzzy extensions of these methods are preferred because of the complexity of the green supplier selection problem and inclusion of both quantitative and qualitative criteria. Also, these criteria may be uncertain and conflict with each other. It is the first time that SWARA-F is combined with MARCOS-F for the green supplier assessment and selection of the best one among them. The effectiveness of the proposed methodology is demonstrated by solving the real selection problem of a company from textile industry. In the problem both classic and green criteria including main and sub-criteria are considered. SWARA-F is used for weighting the evaluation criteria and the rank of each green supplier alternatives is obtained from incomplete information by assessment score calculated from MARCOS-F. The effectiveness of the combination of two methods is verified by sensitivity and comparative analyses. The proposed methodology provides acceptable and satisfactory results in determining the best green supplier namely improving the environmental and cost efficiency evaluation process.

Due to population growth and the expansion of different industries, Iran is confronted with the issue of energy and hydrogen generation for various sectors. According to research, Iran has much potential for renewable energy sources such as wind and solar. Renewable energy is critical for meeting the needs of various industries by producing energy and hydrogen. As a result, this study identified and analyzed development plans for hydrogen production from Iran's renewable energies using SWOT analysis and multi-criteria decision-making (MCDM) techniques. The Stepwise Weight Assessment Ratio Analysis (SWARA) approach was used to weigh the criteria and sub-criteria, and power generation cost was identified as the most critical sub-criteria. Then, the identified strategies were ranked using the gray additive ratio assessment (ARAS-Gray) method. Following that, the gray technique for order of preference by similarity to the ideal solution (TOPSIS-G), the gray complex proportional assessment (COPRAS-G), and the gray simple additive weighting (SAW-G) techniques were used to validate the results. The finding revealed that the strategy of cooperation and coordination between energy investing companies and various industries in Iran to develop hydrogen projects at a minimum cost was recognized as the most efficient strategy in all procedures. As a result, with the cooperation and coordination of companies and various industries in Iran, clean energy and fuel can be produced at a low cost using renewable sources. By implementing this strategy, the fluctuations in energy production caused by renewable sources will be eliminated, and the energy and hydrogen requirements of various industries will be met.

Bus rapid transit (BRT): A simulation and multi criteria decision making (MCDM) approach

Driven by digitalization in supply chains, the use of Collaborative Robots (COBOTs) has become increasingly widespread in recent years. They significantly contribute to process efficiency by working in place of, or in collaboration with, humans in a variety of operations, including welding, painting, assembly and disassembly, transportation, packaging, and palletizing. However, when uncertainty and different criteria are taken into account, decision support systems that compare practical robots based on their suitability for specific needs are inadequate. This study presents a comprehensive multi-criteria decision-making (MCDM) framework for prioritizing COBOTs with different features used in digital supply chain processes. Based on in-depth research in the literature and the opinions of experts working in companies that use relevant robots in the industry, the criteria to be evaluated when selecting COBOT types are identified. The importance of these criteria was determined using the Picture Fuzzy Step-wise Weight Assessment Ratio Analysis (PiF-SWARA) method, which effectively captures the uncertainty in experts’ decisionmaking processes. Subsequently, alternative COBOT types were ranked using the Picture Fuzzy Combinative Distance-Based Assessment (PiFCODAS) approach. This case study, which evaluates the PiF-SWARACODAS concept, reveals that according to expert assessments, cost is the most important criterion in COBOT selection, followed by process quality and space utilization. The findings about the selection of types emphasize that high-efficiency articulated robots operating at high speeds under mass production conditions are the primary priority. These robots are followed by humanoid robots. The third most important are power and force-limiting robots. The fourth and fifth types of COBOTs are hand-guided and safety-monitored stop robots. Validation and sensitivity analyses confirmed the robustness of the results. Overall, the proposed framework not only clarifies the key priorities for manufacturing facilities but also provides a validated decision support tool to align digitalization strategies with the most appropriate COBOT investments.OPEN ACCESS Received: 25/08/2025 Accepted: 15/10/2025 Published: 15/12/2025 An extensive literature review was conducted to examine previous research on COBOT applications in the supply chain, to identify evaluation criteria and alternatives for this study, and to highlight the originality of this study. The concept of COBOT was included in books, journals and conference proceedings accessible through the SCOPUS database. However, the literature search with the related keyword found too many studies. Therefore, the scope was further customized to include different types of COBOT models that can be used throughout the supply chain. To make the literature review process more systematic, the PRISMA methodology, which stands for “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)”, was used. The PRISMA approach, designed by Moher et al. [10], has become widely used among academics in recent years. Sources are analyzed and evaluated according to the determined eligibility criteria. Then, appropriate studies are selected. Table 1lists the keywords used to perform a PRISMA method literature review, along with the number of studies found using these Table 1: Literature search with A total of 1179 studies were found in SCOPUS after searching with the were found. The results were duplicated because some