درخت حوزه‌های تخصصی

The arrangement of machines and how to move them is one of the most important issues in factories and production units, which always imposes a lot of costs on the collections. Although the arrangement of machines is done once over a long period of time, its effects are very widespread. Accordingly, it is necessary to pay more attention to the matter of arrangement. Today, cellular production is also one of the widespread production methods at the industrial level, which requires this precision. The current research aims to produce new arrangements by using artificial neural networks. The way of working is that by using the data related to the number of production parts, the production time of each part, and the group of parts under investigation, as well as the costs of the devices, this clustering is done in 3 modes of 4, 6, and 9. Performing this type of clustering has higher accuracy and speed than other methods, and the results may be somewhat different in each scenario and with each clustering time, which increases flexibility in selection.

Investing in stocks is fraught with long risks that make it tough to manage and predict the choices out there to the investor. Artificial Neural Network (ANN) is a popular method which also incorporates technical analysis for making predictions in financial markets. The purpose of this work is an applied study which is conducted using description based on testing as method. The discussion is established on analytical-computational methods. In this research, the documents and statistics of the Tehran Stock Exchange are used to obtain the desired variables. Descriptive statistics and inferential statistics, as well as Perceptron multi-layer neural networks are utilized to analyze the data of this research. The results of this research show the confirmation of the high prediction accuracy of the Tehran Stock Exchange index compared to other estimation methods by the presented model, which has the ability to predict the total index with less than 1.7% error.

The present study aimed to investigate the impact of organizational entrepreneurship on improving competitive advantage with the mediating role of innovation. The present study was applied in terms of aim, descriptive-survey in terms of data collection method, and quantitative in terms of type of data collected. The statistical population of the study included 75 executive managers of companies operating in the start-up digital industry. Using a convenience random sampling method and Cochran's formula, 63 people were considered as the sample size. Data were analyzed using Smart PLS software. The results obtained from path coefficients and significant coefficients showed that organizational entrepreneurship and competitive advantage have a significant and positive effect on the innovation of start-up digital industries. It was also concluded that organizational entrepreneurship has a positive and significant impact on competitive advantage. It was also found that competitive advantage could mediate the relationship between organizational entrepreneurship and innovation.

Managing supply chain operations in a reliable manner is a significant concern for decision-makers in competitive industries. In recent years consumers and legislation have been pushing companies to design their activities in such a way as to reduce negative environmental impacts more and more. It is therefore important to examine the optimization of total supply chain costs and environmental impacts together. However, because of the recycling of deteriorated products, the environmental impacts of deteriorating items are more significant than those of non-deteriorating ones. The subject of supply chain of deteriorating products, simultaneously considering costs and environment has gained attention in the academia and from the industry. Particularly for deteriorating and seasonal products, such as fresh produce, the issues of timely supply and disposal of the deteriorated products are of high concerns. The objective of this paper is to develop multi objective mathematical model and to propose a new replenishment policy in a centralized supply chain for deteriorating products. In this model, the manufacturer produces a new product and delivers it to a distant market, and then the distributor buys the product and sells it to the end consumers. This study presents a new mathematical model of the location-routing problem (LRP) of facilities in supply chain network (SCN) for deteriorating products through taking environmental considerations, cost, delivery time and customer satisfaction into account across the entire network and customer satisfaction. In order to solve the model, the combination of the two red deer algorithm (RDA) and annealing simulation (AS) was proposed. We then perform the network optimization in SCN and provide some managerial insights. Finally, more promising directions are suggested for future research.

Some cities have unique and special features that have created a strong image of them in the minds of people elsewhere; But there are many cities that, despite their special features, have not been successful in this area. The purpose of this research is to validate the urban brand model in order to develop the tourism industry in Gilan province. The statistical population of the study includes managers and experts of Guilan Cultural Heritage and Tourism Organization and employees working in tourism services offices of Guilan Province. Using a researcher-made questionnaire, 201 of them by Simple random sampling method were selected. Structural equation modeling using LISREL software was used to validate the model. The results of model validation showed that There is no significant relationship between contextual factors and strategies. But there is a significant relationship between other relationships in the model and the relationship between them was confirmed.

The improved model of the Agile Kanban (i-KAM) is developed to enhance the software project monitoring task when employing Agile project management (APM) approach. The i-KAM have been initially verified by 11 knowledge and domain experts. In consequence, it has been reconstructed and enhanced based on the remarks and recommendations provided by the experts. This paper aims to present the final evaluation results of i-KAM achieved from seven software practitioners participated in a focus group. The focus group method was selected because it is an empirical approach used in the evaluation studies conducted in the software engineering (SE) domain. Therefore, this method was employed to obtain the practitioners’ feedback on the proposed model. Results confirm the effectiveness of i-KAM, in which it can assist the project managers and team members in monitoring their projects’ progress effectively. In addition, it is indicated that i-KAM is an applicable model with easy and practical implementation. This study contributes to improve the task of monitoring software development projects within the APM environment. Accordingly, this would systematically facilitate the top managements’ work, and assist in making meaningful decisions regarding to the management of projects’ workflow. Practically, case studies will be carried out in different software development organizations (SDOs) to implement i-KAM in actual projects within real environments