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Stochastic Optimization Inspired by Nature

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Introductory tutorials on nature-inspired heuristics by Dr. Jürgen Branke from the University of Karlsruhe in Germany.

What
  • Summer School
When Jul 18, 2005 09:00 AM to
Jul 31, 2005 06:00 PM
Where ITU Electrical and Electronics Faculty
Contact Name
Contact Phone +90 212 2856471
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Many optimization problems are too complex to be solved to optimality. A promising alternative is to use stochastic heuristics, based on some fundamental principles observed in nature. Examples include evolutionary algorithms, ant colony optimization, or simulated annealing. These methods are widely applicable and have proven very powerful in practice. During the tutorials, such optimization methods based on natural principles are presented, analysed and compared.

Outline

  • General introduction to optimization algorithms
  • Black box optimization
  • No free lunch theorem
  • Search space vs. solution space
  • Representation o Neighborhood
  • Landscape
  • Techniques
  • Simulated Annealing
  • Tabu Search
  • Evolutionary Algorithms
  • Ant Colony Optimization
  • Special topics:
  • Multi-Objective Optimization
  • Constraint handling
  • Parallelization
  • Dynamic environments
  • Integrating heuristic knowledge
  • Use of approximation functions
  • Applications