Abstract
In the fields of engineering technology, economy and systems engineering etc. there are many multi-objective optimization problems. The multi-objective optimization problem is a kind of complex optimization problem that are difficult to solve. Therefore, the thesis proposes themulti-objective optimization genetic algorithm based on Pareto optimal solution database. This algorithm improves the selection operator with a preservation mechanism--data basethat can reservethe optimal solution of each generation of Pareto. As for the Pareto optimal individual in data base, the optimal solution of Pareto operation and the Euclidean distance operation are carried out. Experimentalverification verifies that this algorithm not only effectively avoids the damage caused by selection, cross and mutation operation to Pareto , but has high evolution speed and stable algorithm.
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