The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation
The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation
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DOI：
10.1007/3-540-45356-3_82
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发表时间：
2000-09
期刊：
影响因子：
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通讯作者：
D. Corne;Joshua D. Knowles;M. Oates
中科院分区：
文献类型：
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作者：
D. Corne;Joshua D. Knowles;M. Oates
我们介绍了一种新的多目标进化算法PESA（Pareto包络为基础的选择算法），其中选择和多样性的维护控制通过一个简单的超网格为基础的计划。PESA的选择方法是比较不寻常的，与目前众所周知的多目标进化算法，它往往使用计数的基础上的解决方案在人口中占主导地位的程度。分集保持方法与某些其他方法所使用的方法类似。PESA的主要吸引力是选择和多样性维持的整合，因此基本上相同的技术用于这两项任务。由此产生的算法很容易描述，这里提供了完整的伪代码，作者可以提供真实的代码。我们比较PESA与最近的两个强大的性能MOEAs的一些多目标测试问题最近提出的Deb。我们发现，PESA出现作为最好的方法整体上对这些问题。
We introduce a new multiobjective evolutionary algorithm called PESA (the Pareto Envelope-based Selection Algorithm), in which selection and diversity maintenance are controlled via a simple hyper-grid based scheme. PESA’s selection method is relatively unusual in comparison with current well known multiobjective evolutionary algorithms, which tend to use counts based on the degree to which solutions dominate others in the population. The diversity maintenance method is similar to that used by certain other methods. The main attraction of PESA is the integration of selection and diversity maintenance, whereby essentially the same technique is used for both tasks. The resulting algorithm is simple to describe, with full pseudocode provided here and real code available from the authors. We compare PESA with two recent strong-performing MOEAs on some multiobjective test problems recently proposed by Deb. We find that PESA emerges as the best method overall on these problems.