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4. Nontraditional Optimization Algorithms

4. Nontraditional Optimization Algorithms. Scientists have tried to mimic the nature throughout the history. Nature. Manmade. Nature. Manmade. Crane (bird). Crane (Machine). Nature. Manmade. Crane (bird). Crane (Machine). Fish. Submarine. Nature. Manmade. Crane (bird).

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4. Nontraditional Optimization Algorithms

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  1. 4. Nontraditional Optimization Algorithms

  2. Scientists have tried to mimic the nature throughout the history.

  3. Nature Manmade

  4. Nature Manmade Crane (bird) Crane (Machine)

  5. Nature Manmade Crane (bird) Crane (Machine) Fish Submarine

  6. Nature Manmade Crane (bird) Crane (Machine) Fish Submarine bird Aircraft

  7. Nature Manmade Crane (bird) Crane (Machine) Fish Submarine bird Aircraft Brain processes Microprocessor

  8. Nature Manmade Crane (bird) Crane (Machine) Fish Submarine bird Aircraft Brain processes Microprocessor Biological neural networks Artificial Neural networks

  9. Nature Manmade Crane (bird) Crane (Machine) Fish Submarine bird Aircraft Brain processes Microprocessor Biological neural networks Artificial Neural networks Reproduction process Genetic Algorithms

  10. The nontraditional optimization algorithms are

  11. The nontraditional optimization algorithms are Genetic Algorithms

  12. The nontraditional optimization algorithms are Genetic Algorithms Neural Networks

  13. The nontraditional optimization algorithms are Genetic Algorithms Neural Networks Ant Algorithms

  14. The nontraditional optimization algorithms are Genetic Algorithms Neural Networks Ant Algorithms Simulated Annealing

  15. 4.1 Genetic Algorithms

  16. 4.1 Genetic Algorithms 4.1.(a) Notion of Genetic Algorithms

  17. 4.1 Genetic Algorithms 4.1.(a) Notion of Genetic Algorithms Human

  18. 4.1 Genetic Algorithms 4.1.(a) Notion of Genetic Algorithms Human 1 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 0

  19. 4.1 Genetic Algorithms 4.1.(a) Notion of Genetic Algorithms Human 1 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 0 23 chromosomes

  20. 4.1 Genetic Algorithms 4.1.(a) Notion of Genetic Algorithms Human 1 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 0 23 chromosomes A fetus is formed by a Male(sperm) and female(egg).

  21. 1 0 1 1 1 0 0 1 + 0 1 1 0 0 1 1 0

  22. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0

  23. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0

  24. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0

  25. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 Crossover point

  26. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0

  27. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0

  28. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 0 1 1 1 1 0 0 1

  29. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 0 1 1 1 1 0 0 1

  30. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 0 1 1 1 1 0 0 1

  31. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 1

  32. 1 0 1 1 1 0 0 1 1 0 1 1 1 0 0 1 + + 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 1 0 0 1 0 1 1 1 1

  33. 4.1.(b) Some Basic Facts

  34. 4.1.(b) Some Basic Facts Powerful

  35. 4.1.(b) Some Basic Facts Powerful, wealthy

  36. 4.1.(b) Some Basic Facts Powerful, wealthy, smart

  37. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking

  38. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or

  39. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people

  40. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities.

  41. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities. But, it is random.

  42. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities. But, it is random. (Probability of Selection-Fitness)

  43. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities. But, it is random. A kid may be more mother like or father like.

  44. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities. But, it is random. A kid may be more mother like or father like. But, it is random.

  45. 4.1.(b) Some Basic Facts Powerful, wealthy, smart, good looking, Educated or caring people get more dating opportunities. But, it is random. A kid may be more mother like or father like. But, it is random. (Crossover Point)

  46. Approximately 10% of couples do not have kids since either they opt not to have them or

  47. Approximately 10% of couples do not have kids since either they opt not to have them or they cannot have them biologically.

  48. Approximately 10% of couples do not have kids since either they opt not to have them or they cannot have them biologically. But, it is random.

  49. Approximately 10% of couples do not have kids since either they opt not to have them or they cannot have them biologically. But, it is random. The population can be maintained at a constant level by perfect family planning.

  50. Approximately 10% of couples do not have kids since either they opt not to have them or they cannot have them biologically. But, it is random. The population can be maintained at a constant level by perfect family planning. It is done by limiting 2 kids per family.

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