How to run optimization

• A. Definition of genetic algorithms: Mechanisms of genetics and evolution of living organisms in terms of engineering
  An optimization exploration method to find a solution (solution) to a problem by modeling
• B. Genetic algorithm operation
• 1) Randomly generated population of n chromosomes (candidates for the problem; Start with production quantity combinations).
  ‍2) Each group of individuals (production quantity combination)Each chromosome in(Production quantity) x suitability fCompute (x).
  3) Each group of individuals (production quantity combination)Top suitability in f(x) Select only X
  ‍4) Selected in section '3) 'above XA group of individuals(Production quantity combination)Repeat the steps below until n generations of offspring have been produced
• a. Select 1 parent (asexual reproduction) from the current population of X individuals.
  b. Multiplies by Y to form Y children, but each child applies a mutation in the range of ± σ.
  c. Replace the current group of entities with a new group of child entities.
  d. If not the last n generation, go to step '2) '.
• 5) If up to n generations of offspring are produced, The highest level of suitability for the last generation fGroup of entities in (x)(Production quantity combination)is selected as the year.