Reverse Multi-Objective Robust Design Optimization (R-MORDO) Using Chaos Collocation Based Robustness Quantification for Engine Calibration

Parashar, Sumeet; Clarich, Alberto; Geremia, Paolo; Otani, Asahiko

doi:10.2514/6.2010-9038

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Multiple Criteria Decision Analysis Software

Weistroffer

2016

International Series in Operations Research &Amp; Management Science

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Multiple Criteria Decision Analysis Software

Weistroffer

2016

International Series in Operations Research &Amp; Management Science

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Quantifying and reducing the complexity of multi-line charts as a visual aid in multi-criteria decision-making

Huang,

Siraj

2024

Ann Oper Res

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Multi-line charts are commonly used in multi-criteria decision-making (MCDM) to represent multiple data series on the same graph. However, the presence of conflicting criteria or divergent viewpoints introduces the challenge of accurately interpreting these charts, necessitating thoughtful design to improve their comprehensibility. In this paper, we model these multi-line charts as connected perfect matching bipartite graphs. We propose a metric called the Coefficient of Complexity (CoC) to quantify the complexity of these multi-line charts. In order to reduce the visual complexity of these charts, we propose to minimize the CoC by modeling it as an integer linear optimization problem (reminiscent of the traveling salesman problem). We demonstrate our techniques through multiple real-life case studies, wherein multi-line charts serve as data visualization across various MCDM software tools. Additionally, multi-line charts with specific requirements have been optimized using our approach, showcasing the adaptability and efficacy of our technique. We also formulate the radar chart as a specialized form of the multi-line chart, and adapt our technique to improve its comprehensibility. The proposed CoC and its optimization are important contributions to the field of analytics, as a number of methods use multi-line charts for visual aid. Consequently, enhancing their comprehensibility can facilitate the decision-making process and help decision-makers gain insights.

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