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Zohreh Davarzani,Soheila Staji,Fahimeh Dabaghi-Zarandi 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12
This article deals with solving the flexible job shop scheduling problem in dynamic environment (DFJSSP). In this problem, environment may face with many real time events such as random arrival of jobs or breakdown machine efficiency. Jobs and their operations are processing the machines according to static scheduling in which environment might face with such events. Regarding being NP – hard of the problem , a hybrid of artificial immune and virus evolutionary algorithm are offered to solve it which use the technique of stable action – reaction scheduling . In these algorithms two objective functions are minimized: Efficiency and stability. Efficiency is the objectives value in static scheduling, whereas stability is presented in dynamic scheduling because its purpose is to improve static scheduling, reduce the deviation from the first scheduling, and increase system stability.
Mohammad Tashrifi,Zohreh Davarzani 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4
Today, with the globalization and the competitive element, there are great developments in commerce and banking management. Therefore traditional methods change to the modern ones. Undoubtedly innovative organizations need to be equipped with the advanced information technology and administrative skills. This paper present the quality of electronic services in the improvement of customer relationship in the branches of Khorasan Razavi Melli Bank. 150 questionnaires are distributed among the customers that use electronic services. Data is analyzed by correlation coefficient, regression and SPSS. Results indicate the effect of electronic services on the customer satisfaction, reduction of customer costs and increase security for customers of Melli Bank. At the end some ideas recommend to these branches.
Sima Vosoghi Asl,Zohreh Davarzani,Soheila Staji 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
This article examines navigation of a flying robot inside a building environment in three dimensional spaces in which the size and location of some obstacles are not determined and other obstacles and target can be moving. This article suggests a new method by combining Q-learning algorithm and Monte Carlo algorithm on optimal navigation by the flying robot. The rewards are intended to be maximized when the robot flies in the right route; moreover, the maximum performance power would be measured according to the future predictions and the well-doing of that action would be also measured. Here, this method has been implemented with Webots simulator, and simulated data are analyzed by MATLAB. The simulation results show that control of the policy obtained from Q-learning and Monte Carlo methods is more efficient compared to traditional methods in controlling flying robot navigation.
A Probabilistic Algorithm for MANET Clustering
Fahimeh Dabaghi-Zarandi,Behrouz Minaei-Bidgoli,Zohreh Davarzani 보안공학연구지원센터 2014 International Journal of Future Generation Communi Vol.7 No.6
Mobile ad hoc network (MANET) is a type of ad hoc network that MANET nodes can change their locations and configure by themselves on the fly. Because of mobility the MANET nodes, the management of a large MANET is difficult, therefore, clustering in a MANET is an important technique. A large network is divided into several sub networks applying clustering method. When the topology of the network is dynamic and ad hoc, the process of clustering is very complicated. In this paper, we propose a Probabilistic Algorithm for MANET Clustering (PAMC) to improve the performance of this wireless technology. We simulate our algorithm and evaluate it based on two criteria: the average number of clusters and the average re-affiliation.