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Interactivized: Visual Interaction for Better Decisions With Interactive Multiobjective Optimization
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AI
DOI：10.1109/ACCESS.2022.3161465.png)
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Abstract
En 中文
In today's data-driven world, decision makers are facing many conflicting objectives. Since there is usually no solution that optimizes all objectives simultaneously, the aim is to identify a solution with acceptable trade-offs. Interactive multiobjective optimization methods are iterative processes in which a human decision maker repeatedly provides one's preferences to request computing new solutions and compares them. With these methods, the decision maker can learn about the problem and its limitations. However, advanced optimization software usually offer simple visualization tools that can be significantly improved. On the other hand, current approaches for multiobjective optimization from the visualization community provide superior visualization tools but lack advanced optimization. In this paper, we introduce a new term, interactivize, for integrating interactive multiobjective optimization and interactive visualization and present an interactivized approach supporting decision makers in visually steering interactive multiobjective optimization methods. We integrate state-of-the-art interactive visualization with the process of interactive multiobjective optimization in a visual analytics solution that significantly improves the analysis workflow of decision makers, like comparing selected solutions and specifying new preferences during the iterative solution process. To realize the new interactivized approach, we combine a coordinated multiple views system with DESDEO, an open-source software framework for interactive multiobjective optimization. We demonstrate our interactivized approach on a river pollution problem.
Keywords:
Optimization
Visual analytics
Pareto optimization
Task analysis
Linear programming
Rivers
Pollution
Visual analytics
multiple criteria decision making
interactive optimization