List of Articles Genetic Algorithm

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  1 - Applying genetic algorithm for automatic service identification based on quality metrics
  Jan Mohammad Rajabi saeed parsa masoud bagheri ali akbar
  Service-oriented architecture improves the stability and operational capability of software systems for passive defense measures. Automatic identification of services using quality of service measures ensures the successful deployment of service-oriented architecture an More

  Service-oriented architecture improves the stability and operational capability of software systems for passive defense measures. Automatic identification of services using quality of service measures ensures the successful deployment of service-oriented architecture and is great importance to speed up software development life cycle. Little attention to non-functional requirements, no considerations for concurrent effects of business activities and entities and non-automated ranking of candidate services are the major issues with current approaches. The approach proposed in this paper considers both the business processes and entities, simultaneously to detect services. Applying a genetic algorithm, candidate services are identified based on quality metrics i.e. granularity, coupling, cohesion and convergence. These metrics are obtained from breaking goals to requirements of level. The TOPSIS method is applied to rank the candidate services. The illustrated case study is shown that high quality services can be identified automatically with minimal software developer’s interventions. Manuscript profile
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  2 - Determination of Optimum SVMs Based on Genetic Algorithm in Classification of Hyper spectral Imagery
  farhad samadzadegan hadise hassani
  Hyper spectral remote sensing imagery, due to its rich source of spectral information provides an efficient tool for ground classifications in complex geographical areas with similar classes. Referring to robustness of Support Vector Machines (SVMs) in high dimensional More

  Hyper spectral remote sensing imagery, due to its rich source of spectral information provides an efficient tool for ground classifications in complex geographical areas with similar classes. Referring to robustness of Support Vector Machines (SVMs) in high dimensional space, they are efficient tool for classification of hyper spectral imagery. However, there are two optimization issues which strongly effect on the SVMs performance: Optimum SVMs parameters determination and optimum feature subset selection. Traditional optimization algorithms are appropriate in limited search space but they usually trap in local optimum in high dimensional space, therefore it is inevitable to apply meta-heuristic optimization algorithms such as Genetic Algorithm to obtain global optimum solution. This paper evaluates the potential of different proposed optimization scenarios in determining of SVMs parameters and feature subset selection based on Genetic Algorithm (GA). Obtained results on AVIRIS Hyper spectral imagery demonstrate superior performance of SVMs achieved by simultaneously optimization of SVMs parameters and input feature subset. In Gaussian and Polynomial kernels, the classification accuracy improves by about 5% and15% respectively and more than 90 redundant bands are eliminated. For comparison, the evaluation is also performed by applying it to Simulated Annealing (SA) that shows a better performance of Genetic Algorithm especially in complex search space where parameter determination and feature selection are solve simultaneously. Manuscript profile
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  3 - Multicast computer network routing using genetic algorithm and ant colony
  Mohammad Pourmahmood Aghababa
  Due to the growth and development of computer networks, the importance of the routing topic has been increased. The importance of the use of multicast networks is not negligible nowadays. Many of multimedia programs need to use a communication link to send a packet from More

  Due to the growth and development of computer networks, the importance of the routing topic has been increased. The importance of the use of multicast networks is not negligible nowadays. Many of multimedia programs need to use a communication link to send a packet from a sender to several receivers. To support such programs, there is a need to make an optimal multicast tree to indicate the optimal routes from the sending source to the corresponding sinks.  Providing an optimal tree for routing is a complicated problem. In this paper, we are looking forward a method for routing of multicast networks with considering some parameters such as the cost and delay. Also, this paper has emphasized the issue that every parameter in routing problem has different value for different packets. And in accordance to these parameters optimal routing multicast trees are proposed. To gain this end, the genetic algorithm and ant colony optimization approaches are adopted. The simulation results show that the presented algorithms are able to produce optimal multicast trees subject to the packets. Manuscript profile
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  4 - Using a Hybrid PSO-GA Method for Capacitor Placement in Distribution Systems
  mohammadmahdi Varahram amir mohammadi
  20.1001.1.27170411.1393.6.20.1.9
  In this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient.The particle swarm optimization (PSO) algorithm has shown rapid convergence during the initial stages of a global search but ar More

  In this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient.The particle swarm optimization (PSO) algorithm has shown rapid convergence during the initial stages of a global search but around global optimum, the search process will become very slow. On the other hand, genetic algorithm is very sensitive to the initial population. In fact, the random nature of the GA operators makes the algorithm sensitive to the initial population. This dependence to the initial population is in such a manner that the algorithm may not converge if the initial population is not well selected. This new algorithm can perform faster and does not depend on initial population and can find optimal solutions with acceptable accuracy. Optimal capacitor placement and sizing have been found using this hybrid PSO-GA algorithm. We have also found the optimal place and size of capacitors using GA and PSO separately and compared the results. Manuscript profile
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  5 - Scheduling tasks in cloud environments using mapping framework - reduction and genetic algorithm
  nima khezr nima jafari novimipour
  20.1001.1.27170414.1397.10.37.2.7
  Task scheduling is a vital component of any distributed system such as grids, clouds, and peer-to-peer networks that refer tasks to appropriate resources for execution. Common scheduling methods have disadvantages such as high time complexity, inconsistent execution of More

  Task scheduling is a vital component of any distributed system such as grids, clouds, and peer-to-peer networks that refer tasks to appropriate resources for execution. Common scheduling methods have disadvantages such as high time complexity, inconsistent execution of input tasks, and increased program execution time. Exploration-based scheduling algorithms to prioritize tasks from Manuscript profile
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  6 - Routing of Multipartite Computer Networks Using Ant Genetic Algorithm
  Mohammad Pourmahmood Aghababa amin bahadorani baghbaderani
  20.1001.1.27170411.1396.9.31.1.2
  With the growth and development of computer networks, the importance of routing has become a thing of the past. The importance of using multi-sectoral networks cannot be ignored today. Many multimedia applications require sending a packet from one source to multiple des More

  With the growth and development of computer networks, the importance of routing has become a thing of the past. The importance of using multi-sectoral networks cannot be ignored today. Many multimedia applications require sending a packet from one source to multiple destinations over a communication network. To support such programs, you need to create an optimal multipart tree , Which indicates the optimal routes to reach from one sender source to several desired destinations. Manuscript profile
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  7 - The aware genetic algorithm of the best member, applied to graph coloring and metric-dimension of the graph problems
  mahmood amintoosi Hashem Ezzati
  20.1001.1.27170414.1399.12.43.10.1
  Genetic algorithm is one of the most famous methods for solving Combinatorial Optimization Problems. It had various applications in different field of studies such as Electronics, Computer Science and Mathematics and still has. In this algorithm, the population members More

  Genetic algorithm is one of the most famous methods for solving Combinatorial Optimization Problems. It had various applications in different field of studies such as Electronics, Computer Science and Mathematics and still has. In this algorithm, the population members which contribute for producing the next generation are selected according to their fitness values. The combination of the members is through Crossover Operator; And in some versions a few of the best members migrate to the next generation directly. Normally, the weak members of population may participate to the next generation. In this study, the combination operators are aware of the best member of generation; Only those child which are as good as the best member, are allowed to form the next generation. The proposed method is applied on graph coloring and finding metric-dimension of graph problems. The results are compared with the common genetic algorithm. Experimental results shows the superior performance of the proposed method in comparison to common genetic algorithm. Manuscript profile
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  8 - A Task Mapping and Scheduling Algorithm based on Genetic Algorithm for Embedded System Design
  mohadese nikseresht Mohsen Raji
  20.1001.1.27170414.1400.13.47.12.8
  Embedded system designers face numerous design requirements and objectives (such as runtime, power consumption and reliability). Since meeting one of these requirements mostly contradicts other design requirements, it seem to be inevitable to apply multi-objective appr More

  Embedded system designers face numerous design requirements and objectives (such as runtime, power consumption and reliability). Since meeting one of these requirements mostly contradicts other design requirements, it seem to be inevitable to apply multi-objective approaches in various stages of designing embedded systems, including task scheduling step. In this paper, a multi-objective task mapping and scheduling in the design stage of the embedded system is presented. In this method, tasks are represented by task graphs assuming that the hardware architecture platform is given and determined. In order to manage the dependencies between tasks in the task graph, a segmentation method is used, in which the tasks that can be executed simultaneously are specified in a segment and is considered in the scheduling process. In the proposed method, the task mapping and scheduling problem is modeled as a genetic algorithm-based multi-objective optimization problem considering execution time, energy consumption, and reliability. In comparison to similar previous works, the proposed scheduling method respectively provides 21.4%, 19.2%, and 20% improvement in execution time, energy consumption, and reliability. Applying a multi-objective helps the designer to pick out the best outcome according to different considerations. Manuscript profile
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  9 - Presenting the model for opinion mining at the document feature level for hotel users' reviews
  ELHAM KHALAJJ shahriyar mohammadi
  20.1001.1.27170411.1400.13.49.6.1
  Nowadays, online review of user’s sentiments and opinions on the Internet is an important part of the process of people deciding whether to choose a product or use the services provided. Despite the Internet platform and easy access to blogs related to opinions in the More

  Nowadays, online review of user’s sentiments and opinions on the Internet is an important part of the process of people deciding whether to choose a product or use the services provided. Despite the Internet platform and easy access to blogs related to opinions in the field of tourism and hotel industry, there are huge and rich sources of ideas in the form of text that people can use text mining methods to discover the opinions of. Due to the importance of user's sentiments and opinions in the industry, especially in the tourism and hotel industry, the topics of opinion research and analysis of emotions and exploration of texts written by users have been considered by those in charge. In this research, a new and combined method based on a common approach in sentiment analysis, the use of words to produce characteristics for classifying reviews is presented. Thus, the development of two methods of vocabulary construction, one using statistical methods and the other using genetic algorithm is presented. The above words are combined with the Vocabulary of public feeling and standard Liu Bing classification of prominent words to increase the accuracy of classification Manuscript profile