To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Simultaneously visualizing the decision and objective space of continuous multi-objective optimization problems (MOPs) recently provided key contributions in understanding the structure of their landscapes. For the sake of advancing these recent findings, we compiled all state-of-the-art visualization methods in a single R-package (moPLOT). Moreover, we extended these techniques to handle three-dimensional decision spaces and propose two solutions for visualizing the resulting volume of data points. This enables – for the first time – to illustrate the landscape structures of three-dimensional MOPs. However, creating these visualizations using the aforementioned framework still lays behind a high barrier of entry for many people as it requires basic skills in R. To enable any user to create and explore MOP landscapes using moPLOT, we additionally provide a dashboard that allows to compute the state-of-the-art visualizations for a wide variety of common benchmark functions through an interactive (web-based) user interface.
Details
Original language | English |
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Title of host publication | Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings |
Editors | Hisao Ishibuchi, Qingfu Zhang, Ran Cheng, Ke Li, Hui Li, Handing Wang, Aimin Zhou |
Pages | 632-644 |
Number of pages | 13 |
Publication status | Published - 2021 |
Peer-reviewed | Yes |
External IDs
Scopus | 85107304508 |
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ORCID | /0000-0003-3929-7465/work/142241491 |
Mendeley | af01d2ca-a8cc-35b0-a2d0-ddaf706a55ba |
Keywords
ASJC Scopus subject areas
Keywords
- Continuous optimization, Graphical user interface, Multi-objective optimization, R-package, Software, Visualization