4.5 Article

Task-based visual analytics for interactive multiobjective optimization

期刊

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
卷 72, 期 9, 页码 2073-2090

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/01605682.2020.1768809

关键词

Decision maker; preference information; multiple criteria optimization; visualization; task taxonomy; user interface

资金

  1. Academy of Finland [311877]
  2. BMVIT
  3. BMDW, Styria
  4. SFG
  5. Vienna Business Agency [854174]

向作者/读者索取更多资源

This study examines how visual interaction techniques from visual analytics can be applied in interactive multiobjective optimization methods, aiming to increase awareness and applicability of interactive methods for solving real-world problems. The authors introduce seven high-level tasks and provide an example of their implementation.
We study how visual interaction techniques considered in visual analytics can be utilized when implementing interactive multiobjective optimization methods, where a decision maker iteratively participates in the solution process. We want to benefit from previous research and avoid re-inventing ideas. Our aim is to widen awareness and increase the applicability of interactive methods for solving real-world problems. As a concrete approach, we introduce seven high-level tasks that are relevant for interactive methods. These high-level tasks are based on low-level tasks proposed in the visual analytics literature. In addition, we give an example on how the high-level tasks can be implemented and demonstrate this in the context of a real-world multiobjective optimization problem related to wastewater treatment plant operation. Finally, we make recommendations for implementations of interactive methods. We conclude that task-based visual analytics can help in implementing interaction between human decision makers and interactive multiobjective optimization methods.

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