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The false location of airports is one of the most important issues and challenges that we face on some airports, finding scientific solutions to optimize airports, to achieve travelers, including these challenges. The main purpose of this research is to provide a metaheuristic technique for locating the construction of airport and compared with the results of the seca model and the Copras Method. The metaheuristic technique is based on new multi-criteria decision making techniques, aimed at prioritizing research alternatives and its difference with the rest of the methods is to use statistical methods and now it is possible to understand and simply process its process. The statistical population of this research is (experts and management in Iran airport and air Navigation Company). After research, alternatives were selected based on the opinions of experts who included five provinces of the country, as well as 10 standard indicators, including the average income per year, the population of the province and ... who were extracted from the questionnaire as input. Finally, the provinces were prioritized according to different ways, all results based on choosing Isfahan province as the right province and Najaf Abad city as the final alternative

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In this paper the pricing of reverse products in a two-level closed-loop supply chain is considered and a game theory approach is used to solve it. Pricing is a sensitive and vital issue for businesses. In the market of reverse products, this issue will be much more difficult and complex due to difficulties associated with collecting and re-manufacturing processes. On the other hand, the use of the internet and direct channels for collecting products from customers alongside traditional retailers is an important issue that requires management and coordination. The proposed price for buying second-hand and defective products from customers should be high enough to convince them that returning the products has more benefits than discarding or keeping them at home. At the same time, the price should be low enough to make it economically viable for producers to carry out the repair and re-manufacturing operations and resell them in the direct supply chain for the producer. The use of game theory, where the decisions of one player affect the decisions and outcomes of other players as well as their outcomes, is a suitable method for solving the problem of pricing reverse products in a two-level closed-loop supply chain

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Leukemia is one of the most common and dangerous types of cancer in the world. In many cases, the disease is curable if detected in its early stages. One of the effective tools for early detection is the analysis of microarray data, which measures the expression of thousands of genes simultaneously. However, the large volume of features and the presence of noise make the analysis process complex and time-consuming. Therefore, the selection of effective genes plays a key role in increasing the accuracy and reducing the computational cost of learning models. In this paper, a two-step hybrid approach is presented for feature selection and classification of leukemia types. In the first step, the features are filtered using the mutual information criterion and the genes with the highest correlation with the disease label are selected. In the second step, the XGBoost model is used to rank and stably select the features to identify the genes that are most important in different iterations. In the final stage, classification will be performed using the temporal fusion transformer method, which allows for fast and efficient learning of complex patterns among selected genes. Experimental results on real microarray datasets show that the proposed method outperforms the baseline methods with an accuracy of 99.2% and has been able to identify key genes effective in differentiating leukemia types by effectively reducing the data dimensions.

 

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In this paper, we investigate a solution procedure for a fuzzy linear fractional optimization problem in which the input parameters are considered as convex fuzzy numbers. By applying a specific fuzzy ranking method which is based on the α-cut concept, and according to Charnes and Cooper’s approach of variable transformation, the solution of the original fuzzy linear fractional optimization model is transformed to the solution of at most two semi-infinite linear programs that are dis similar among themselves via a sign in a constraint and in the objective function. An appropriate cutting plane algorithm(CPA) of Fang is uti lized to obtain the optimal solution of the semi-infinite linear programs. Further, the application of our provided algorithm in facility location theory is discussed properly. Finally, an illustrative example is given to clarify the developed solution procedure.