Research Article
A Simplified Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization
Algorithm 1
The framework of the algorithm SHEA.
| Input: | | MaOP(1) | | A stopping criterion | | : the number of weight vectors | | : the number of external population | | : the number of weight vectors in the neighborhood of each weight vector, | | : the number of the solutions with largest hypervolume selected in neighbors, | | : a set of uniformly distributed weight vectors | | Output: External population | | Initialization: Generate an initial population randomly; set ; determine by a problem-specific method; determine closest weight vectors to each vector | | While the stopping criterion is not met do | | Calculate the proposed hypervolume of nondominated solutions. | | Fordo | | if rand < J then | | | | else | | | | end if | | Choose and from according to the selection operator in Section 2.2. | | Use and to generate offspring , and set . | | Useto Update: For , if , then set . | | End for | | Set. | | Use the updated strategy to update . | | Use the updated strategy of external population of Section 2.3 to update . | | End while |
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