Mathematical Problems in Engineering / 2015 / Article / Alg 1

Research Article

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

Algorithm 1

The general framework of EA2DGO.
(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.
(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
(15)  End For
(16)   Output