Excellence in Research and Innovation for Humanity
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@article{(International Science Index):http://waset.org/publications/2679,
  title    = {Combined Simulated Annealing and Genetic Algorithm to Solve Optimization Problems},
  author    = {Younis R. Elhaddad},
  country   = {Spain},
  institution={UAM},
  abstract  = {Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {6},
  number    = {8},
  year      = {2012},
  pages     = {1047 - 1049},
  ee        = {http://waset.org/publications/2679},
  url       = {http://waset.org/Publications?p=68},
  bibsource = {http://waset.org/Publications},
  issn      = {PISSN:2010-376X, EISSN:2010-3778},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 68, 2012},
}