Browsing by Subject "Multi objective evolutionary algorithms"

Now showing items 1-5 of 5

    • Article  

      Intelligent search in social communities of smartphone users 

      Konstantinidis, Andreas; Zeinalipour-Yazdi, Constantinos D.; Andreou, Panayiotis G.; Samaras, George S.; Chrysanthis, Panos K. (2013)
      Social communities of smartphone users have recently gained significant interest due to their wide social penetration. The applications in this domain, however, currently rely on centralized or cloud-like architectures for ...
    • Article  

      A multi-objective evolutionary algorithm for the deployment and power assignment problem in wireless sensor networks 

      Konstantinidis, Andreas; Yang, K.; Zhang, Q.; Zeinalipour-Yazdi, Constantinos D. (2010)
      A Wireless Sensor Network (WSN) design often requires the decision of optimal locations (deployment) and transmit power levels (power assignment) of the sensors to be deployed in an area of interest. Few attempts have been ...
    • Conference Object  

      Multi-objective query optimization in smartphone social networks 

      Konstantinidis, Andreas; Zeinalipour-Yazdi, Constantinos D.; Andreou, Panayiotis G.; Samaras, George S. (2011)
      The bulk of social network applications for smart phones (e.g., Twitter, Face book, Foursquare, etc.) currently rely on centralized or cloud-like architectures in order to carry out their data sharing and searching tasks. ...
    • Conference Object  

      Optimal graph design using a knowledge-driven multi-objective evolutionary graph algorithm 

      Nicolaou, Christos A.; Kannas, Christos C.; Pattichis, Constantinos S. (2009)
      Designing appropriate graphs is a problem frequently occurring in several common applications ranging from designing communication and transportation networks to discovering new drugs. More often than not the graphs to be ...
    • Conference Object  

      A parallel implementation of a multi-objective evolutionary algorithm 

      Kannas, Christos C.; Nicolaou, Christos A.; Pattichis, Constantinos S. (2009)
      Multi-objective Evolutionary Algorithms (MOEAs) have features that can be exploited to harness the processing power offered by modern multi-core CPUs. Modern programming languages offer the ability to use threads and ...