A multiobjective evolutionary algorithm using dynamic weight design method
A multiobjective evolutionary algorithm using dynamic weight design method
复制标题
一种采用动态权重设计方法的多目标进化算法
DOI：
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发表时间：
2012-05
影响因子：
1
通讯作者：
Tan, Kay Chen
中科院分区：
文献类型：
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作者：
Gu, Fangqing;Liu, Hai-lin;Tan, Kay Chen
。在大多数基于聚合目标的多目标进化算法（MOEA）中，权重向量是用户提供的或随机生成的，并且它们在算法中是静态的。如果Pareto前沿（PF）形状不复杂，算法可以（cid：12）找到一组沿PF均匀分布的Pareto最优解；否则，他们可能会失败。提出一种基于当前非支配解投影和等距插值的动态权重设计方法。即使PF很复杂，我们也可以通过这种方法(cid:12)找到均匀分布的Pareto最优解。构建了一些测试实例来比较使用动态权重设计方法的 MOEA/D 与 MOEA/D 的性能。结果表明，动态权重设计方法可以显着提高算法的性能。
. In most multiobjective evolutionary algorithms (MOEA) based on aggregating objectives, the weight vectors are user-supplied or generated randomly, and they are static in the algorithms. If the Pareto front (PF) shape is not complex, the algorithms can (cid:12)nd a set of uniformly distributed Pareto optimal solutions along the PF; otherwise, they might fail. A dynamic weight design method based on the projection of the current nondominant solutions and equidistant interpolation is proposed in this paper. Even if the PF is complex, we can (cid:12)nd evenly distributed Pareto optimal solutions by this method. Some test instances are constructed to compare the performance of the MOEA/D using dynamic weight design method with that of MOEA/D. The results indicate that the dynamic weight design method can dramatically improve the performance of the algorithms.