List of Articles زمانبندی

• Open Access Article
  • Abstract Page
  • Full-Text
  
  1 - Enhancing Efficiency and Organizational Knowledge in Assembly Lines Using Discrete-event Simulation Techniques
  Moslem Fadaei Hadi Heydari Ghare Bagh Sedigh Reisi
  10.7508/jstpi.2015.02.008
  In today’s competitive market, companies must work closely with their customers and suppliers if they want to survive and improve their own performance and to provide a better response to market forces. In a typical supply chain, information flow is more important than More

  In today’s competitive market, companies must work closely with their customers and suppliers if they want to survive and improve their own performance and to provide a better response to market forces. In a typical supply chain, information flow is more important than the other two involved flows including material flow and cash flow. It can be lead to enhance organizational knowledge. The main purpose of the research, is to identify, analyse and improve the performance of an assembly line using simulation techniques. Many factors, such as setup time, operating time, failure rate, repair rate, and production rate, can cause data to be non-stationary. Therefor, in order to analyse such complicated systems it is necessary to apply simulation techniques. The most important properties of an assembly line including bottlenecks, cycle time, buffers capacities, and the number of finished products in a given time period are investigated in the research. After data gathering, and building an appropriate simulation model, the simulation experiments were done with Enterprise Dynamic software. The simulation model is implemented and tested against real-world data and is demenostrated by a numerical example. Then, the bottlenecks and performance measures including throughput time and waiting time are identified and analysed in order to develop a new scenario in which opportunities for improvements are presented. The results show significant improvements in terms of reducing waiting time and increasing efficiencies. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  2 - Solve the issue of project scheduling in a steady state with resource constraints and timing of delivery intervals
  Meysam Jafari Eskandari rozbeh azizmohammadi
  Due to considering the real conditions of project and solving manager’s problems, the primary methods development of scheduling for projects has recently drawn researcher’s attentions so that these methods are looking for finding optimal sequence to realize project goal More

  Due to considering the real conditions of project and solving manager’s problems, the primary methods development of scheduling for projects has recently drawn researcher’s attentions so that these methods are looking for finding optimal sequence to realize project goals and to provide its constraints such as dependence, resource constraint (renewable and non-renewable). The importance of these issues has practically and theoretically led researchers to do much efforts on different conditions of issues for project schedule, various methods to solve and or to develop each of them. In this research based on selection of some executive methods for any activity with renewable and non-renewable resource and considering prerequisite relation from kind of start to end and having delivery time for any activity in two time periods that has been provided with regard to delivery time of penalty cost with delay or without delay. The presented model has been solved in small scale by gams software and in small, medium and large scale using meta-heuristic Methods of NSGA ll and cuckoo after coding in software of matlab 2013. The comparison of the answer obtained from the above algorithm indicates the better performance of genetic algorithm in most indexes and cuckoo algorithm has superiority on time index of problem solving. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  3 - Improve security in cloud computing infrastructure using block chain protocol
  Mohsen Gerami Vahid Yazdanian Siavash Naebasl
  10.61186/jstpi.34504.19.76.1
  Security in cloud computing is very important, cloud computing security is a set of computer security and network security in general is information security and when a processing task by using the virtual machine scheduling algorithm in the cloud for processing Unloadi More

  Security in cloud computing is very important, cloud computing security is a set of computer security and network security in general is information security and when a processing task by using the virtual machine scheduling algorithm in the cloud for processing Unloading will be This virtual machine will not be able to distinguish the normal mobile user from attackers, thus violating the privacy and security of the transmitted data, so after determining the unloading strategy, the China block can be used in information security. And the information of each server is encapsulated and unloaded in the form of a block. In this research, a proposed solution is presented, which is the combination of China blockchain and cloud computing to increase security and efficiency. The proposed solution is implemented and evaluated in order to evaluate its efficiency increase compared to other existing solutions. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  4 - A Multi-Objective Differential Evolutionary Algorithm-based Approach for Resource Allocation in Cloud Computing Environment
  Saeed Bakhtiari Mahan Khosroshahi
  In recent years, the cloud computing model has received a lot of attention due to its high scalability, reliability, information sharing and low cost compared to separate machines. In the cloud environment, scheduling and optimal allocation of tasks affects the effectiv More

  In recent years, the cloud computing model has received a lot of attention due to its high scalability, reliability, information sharing and low cost compared to separate machines. In the cloud environment, scheduling and optimal allocation of tasks affects the effective use of system resources. Currently, common methods for scheduling in the cloud computing environment are performed using traditional methods such as Min-Min and meta-heuristic methods such as ant colony optimization algorithm (ACO). The above methods focused on optimizing one goal and do not estimate multiple goals at the same time. The main purpose of this research is to consider several objectives (total execution time, service level agreement and energy consumption) in cloud data centers with scheduling and optimal allocation of tasks. In this research, multi-objective differential evolution algorithm (DEA) is used due to its simple structure features and less adjustable parameters. In the proposed method, a new approach based on DEA to solve the problem of allocation in cloud space is presented which we try to be effective in improving resource efficiency and considering goals such as time, migration and energy by defining a multi-objective function and considering mutation and crossover vectors. The proposed method has been evaluated through a CloudSim simulator by testing the workload of more than a thousand virtual machines on Planet Lab. The results of simulation show that the proposed method in comparison with IqrMc, LrMmt and FA algorithms, in energy consumption by an average of 23%, number of migrations by an average of 29%, total execution time by an average of 29% and service level agreement violation (SLAV) by an average of 1% has been improved. In this case, use of the proposed approach in cloud centers will lead to better and appropriate services to customers of these centers in various fields such as education, engineering, manufacturing, services, etc. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  5 - Improving the load balancing in Cloud computing using a rapid SFL algorithm (R-SFLA)
  Kiomars Salimi Mahdi Mollamotalebi
  Nowadays, Cloud computing has many applications due to various services. On the other hand, due to rapid growth, resource constraints and final costs, Cloud computing faces with several challenges such as load balancing. The purpose of load balancing is management of th More

  Nowadays, Cloud computing has many applications due to various services. On the other hand, due to rapid growth, resource constraints and final costs, Cloud computing faces with several challenges such as load balancing. The purpose of load balancing is management of the load distribution among the processing nodes in order to have the best usage of resources while having minimum response time for the users’ requests. Several methods for load balancing in Cloud computing have been proposed in the literature. The shuffled frog leaping algorithm for load balancing is a dynamic, evolutionary, and inspired by nature. This paper proposed a modified rapid shuffled frog leaping algorithm (R-SFLA) that converge the defective evolution of frogs rapidly. In order to evaluate the performance of R-SFLA, it is compared to Shuffled Frog Leaping Algorithm (SFLA) and Augmented Shuffled Frog Leaping Algorithm (ASFLA) by the overall execution cost, Makespan, response time, and degree of imbalance. The simulation is performed in CloudSim, and the results obtained from the experiments indicated that the proposed algorithm acts more efficient compared to other methods based on the above mentioned factors. Manuscript profile