The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Algorithm 1

The general framework of EA²DGO.

(1)  Begin

(2)  Input: NP, NOP, , CR, OMR, Max_Fes, hl, tl, times, , and ; where NP denotes the size

  of function optimization population; NOP denotes the size of operator generating

   population; denotes scaling factor; CR denotes the probability of crossover; OMR denotes

   the probability of Mutation for operators in operator generating population; Max_FEs

   denotes the max number of function calls; hl is the of head length of chromosome in new

   encoding scheme MEP; tl is the tail length; times denotes the number of repeat times which

   randomly select individuals for mutation manipulation from population in unit of function

   optimization; is the terminal symbol set; is the function symbol set.

(3)   

(4)   Create the function optimization population , ,

(5)   Create the genetic operators population , ,

(6)   , ,

(7)   Evaluate , ,

(8)   For   to Max_FES Do

(9)    Find the best in the function optimization population

(10)     Call the unit of function optimization

(11)    If    Then

(12)      Call the unit of automatically designing genetic operators

(13)    End If

(14)    

(15)   End For

(16)    Output

(17)  End