首页> 外文会议>International conference on parallel problem solving from nature >One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes
【24h】

One PLOT to Show Them All: Visualization of Efficient Sets in Multi-objective Landscapes

机译:一个可以全部显示的图:多目标景观中有效集合的可视化

获取原文

摘要

Visualization techniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global optimality and even for the few available landscape visualizations, e.g., cost landscapes, glob-ality is the main criterion. In contrast, the recently proposed gradient field heatmaps (GFHs) emphasize the location and attraction basins of local efficient sets, but ignore the relation of sets in terms of solution quality. In this paper, we propose a new and hybrid visualization technique, which combines the advantages of both approaches in order to represent local and global optimality together within a single visualization. Therefore, we build on the GFH approach but apply a new technique for approximating the location of locally efficient points and using the divergence of the multi-objective gradient vector field as a robust second-order condition. Then, the relative dominance relationship of the determined locally efficient points is used to visualize the complete landscape of the MOP. Augmented by information on the basins of attraction, this Plot of Landscapes with Optimal Trade-offs (PLOT) becomes one of the most informative multi-objective landscape visualization techniques available.
机译:连续多目标优化问题(MOP)决策空间的可视化技术在研究中非常匮乏。长期以来,所有技术都集中在全局最优性上,甚至对于少数可用的景观可视化(例如成本景观),全局性也是主要标准。相反,最近提出的梯度场热图(GFHs)强调了局部有效集的位置和吸引盆地,但在解质量方面忽略了集的关系。在本文中,我们提出了一种新的混合可视化技术,该技术结合了两种方法的优点,以便在单个可视化中一起表示局部和全局最优。因此,我们建立在GFH方法的基础上,但应用了一种新技术来逼近局部有效点的位置,并将多目标梯度向量场的散度用作鲁棒的二阶条件。然后,使用确定的局部有效点的相对优势关系来可视化MOP的完整景观。通过有关吸引盆地的信息的增强,该具有最佳权衡的景观图(PLOT)成为可用的信息最丰富的多目标景观可视化技术之一。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号