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Selection of parent solutions for breeding 4.
An initial population of parent solutions is generated at random.
For each new solution to be produced, a pair of "parent" solutions is selected for breeding from the pool selected previously.
(iii) Crossover process Two crossover processes are discussed below: Single-point crossover: For each pair of parent solutions, (PY_1=(py_{11},ldots2},py_{1m}y_{1m})) and (PY_2=(py_{21},ldots2},py_{2m}y_{2m})), selected for crossover, an integer position k is selected randomly in the range [1, m], for crossover operation, where m is the length of a solution.
In the next step, a pair of parent solutions will be picked from the selected parents to generate a new solution with crossover operation; meanwhile, mutation(s) can be optionally applied to certain element(s) within a parent individual to generate a new one.
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The crossover operator combines parts of two parent solutions to create a new one.
The first one, synthesizes and transmits the genetic patrimony (heritage) of the parent solutions using their statistical indicators.
In error diagnosis mutation operator, first we copy the nucleotide s iparent and connection information c iparent of a parent solution to the s ichild and c ichild of a child solution for all i (1 ≤ i ≤ N ), respectively; here we copy the c iparent, which is assigned to the parent solution by a direct problem solver, to the child solution.
A thorough rheological characterization of the blends and their parent solutions has been performed.
Then, some variation operators are in charge of modifying current solutions which is usually called parent solutions and their group called parent population.
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