Research Article
An Optimization Framework of Multiobjective Artificial Bee Colony Algorithm Based on the MOEA Framework
Algorithm 1
Unity procedure of metaheuristics.
| Step 1: Initialization | | Initialize parameters and solution set , iteration index k = 0. | | Step 2: Candidate generation | | Generate candidate set according to generation rules and sampling distributions. | | Step 3: Update solution/parameter set | | Update solution set according to candidate set , previously obtained information and algorithm parameters. Update algorithm parameters as well. | | Step 4: Termination conditions | | If termination conditions are satisfied, stop and exit; otherwise return to Step 2. |
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