Reducing the manufacturing costs of the products is considered of the main factors for lead-acid battery (LAB) manufacturers 'sustainability and survival in the automotive industry. Then in order to meaningfully decrease the due costs and enhance the competitive potential of the manufacturers in this field, it’s important to choose the suitable sites for recycling centers in this industry's supply chain. In the present study, data envelopment analysis (DEA) has been utilized for evaluating and choosing the recycling centers as befitting for the supply chain of LABs in the automotive industry. Pursuant to DEA and a set of criteria, as being critical for decision makers in this filed, various locations are evaluated. As this method prescribes, the locations are ranked using the maximum scores of efficiencies and after that, more appropriate centers are picked and the inappropriate ones get removed. A LAB supply chain related case study in the automotive industry has been employed for evaluating the influencing power and efficiency of proposed method and following that, a number of beneficial management results have been extracted. پرونده مقاله

One of the most appropriate and efficient methods for evaluating the performance of homogenous decision-making units (DMU) is data envelopment analysis (DEA). Traditional DEA models are only able to evaluate DMUs with deterministic inputs and outputs, while in real-world problems, data are usually uncertain. So far, various approaches have been introduced to overcome the uncertainty of data. In this paper, two robust DEA models is presented to evaluate the performance of systems with continuous uncertain data under constant return to scale (CRS) and variable return to scale (VRS) conditions. The main advantage of the proposed robust DEA models over the previous robust DEA models is that they are able to formulate uncertainty in both input and output data. Moreover, these models are also developed directly on basic traditional DEA models (not alternative models). To demonstrate the applicability of two developed robust models, a numerical example is presented and the efficacy of models is exhibited. پرونده مقاله

Wheat is a strategic crop; the prosperity of production improves any country's economy. In recent years, Iran has faced a significant decrease in wheat production, so it is important to conduct a study in this sector and provide a suitable solution to improve the concerns. A dynamic network model is presented to calculate efficiency for agricultural farmlands over 6 years. This model considers the every-other-year farming method, indirect input part of that is used in one year and the rest in the following years, and the complex relations of wheat production. Finally, to prove the applicability of the presented model, a case study of wheat fields in the northwest of Iran has been selected, and the desired model has been implemented. The results show Zanjanrod performs at the highest efficiency level, followed by Takestan. پرونده مقاله

Performance management encompasses important activities aimed at fostering effective and efficient behaviors within an organization. Performance evaluation, as one of the tools of performance management, can serve as a robust foundation for decision-making concerning personnel affairs, such as promotions, transfers, demotions, dismissals, and salary increases or decreases. Performance evaluation indicators for chicken meat suppliers in the city of Arak were identified. To collect opinions of chicken meat store managers (24 stores), instruments such as questionnaires were employed. Fuzzy Likert Scale (FLS) was utilized to convert verbal data obtained from the questionnaires. Following the validation of the questionnaire, fuzzy set theory and fuzzy decision-making techniques were used to rank the studied suppliers (six suppliers). Data analysis in MATLAB determined that Supplier 6 (Dorsa Chicken Company) exhibited the best performance, while Supplier 2 (Fakhrar Company) demonstrated the poorest performance. پرونده مقاله