Research Article
A Search History-Driven Offspring Generation Method for the Real-Coded Genetic Algorithm
Algorithm 1
Search history-driven crossover for RCGA.
Input: population , population size , | Archive , archive size , | Score , | Generation ID | Output: estimated global optimum | //initialization | (1) | individuals in are randomly initialized | | //fitness evaluation | (2) | eval | | //archive update | (3) | archiveUpdate ; | (4) | While termination criterion is not satisfied do | (5) | | | //SHX | (6) | parentSelection , ; | (7) | | (8) | offspringGeneration ; | (9) | offspringSelection , ; | | //fitness evaluation | (10) | eval | | //survivor selection | (11) | survivorSelection ; | (12) | | | //archive update | (13) | archiveUpdate ; | (14) | end | (15) | Return . |
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