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This chapter briefly introduces basic optimization concepts. Optimization problems exist in our everyday life. We often wonder about the route with less traffic to work, the less money to spend in various activities, or the best work schedule. Optimization can be thought as the art of making good decisions. In more precise manner, we may define optimization as the process of changing a system's state (or values of some unknown variables) toward a state of a minimum or maximum property. Several optimization problems exist in the whole engineering domain. A common problem in antennas design is to find the best geometry for a given antenna, while in wireless communications the association between a base station and user in an optimal manner is a very popular optimization problem.

Chapter Contents:

  • 1.1 Optimization algorithms
  • 1.1.1 Deterministic algorithms
  • 1.1.2 Stochastic algorithms
  • 1.2 Evolutionary algorithms
  • 1.2.1 Encoding
  • 1.2.2 Boundary conditions constraint handling methods
  • 1.2.3 The no free lunch theorem
  • 1.3 Objective functions
  • 1.3.1 Common benchmark functions
  • Unimodal functions
  • Multimodal functions
  • 1.4 Comparison metrics
  • 1.4.1 Nonparametric tests
  • 1.4.2 Signature of an algorithm
  • 1.5 Multi-objective algorithms
  • 1.5.1 Fuzzy decision maker
  • 1.5.2 Performance indicators for MOEAs
  • 1.6 Discussion-open issues
  • References

Inspec keywords: optimisation; evolutionary computation; antennas

Other keywords: emerging evolutionary algorithms; maximum property; optimization problems; minimum propert; antennas design; optimization concepts; wireless communications

Subjects: Optimisation techniques; Single antennas

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