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The secret weapon of decision maps: How to use animation to explore the delicate balance between five goals?
In various complex decision-making scenarios, how to balance multiple goals has always been a challenge. With the advancement of science and technology, Interactive Decision Maps (IDM) technology emerged as the times require and has become a powerful tool for decision makers (DM). This technology provides a visual solution for multi-objective optimization by approximating the Edgeworth-Pareto Hull (EPH) of the feasible goal set, allowing users to intuitively analyze different goals. interaction between them.
EPH is a practical tool that helps users weigh multiple choices and understand the consequences of each choice.
The concept of EPH is that this set of feasible targets can be expanded to include all target points dominated by it. This structure allows decision makers to work in a more stable environment because EPH behaves more stably to disturbances in the data than the Pareto front. IDM technology supports fast online display, allowing users to select two targets for comparison while observing the impact of changes in other targets on the results.
This interactive decision map not only provides a visual display of data, but also makes the decision-making process more vivid through dynamic slicing. As the user moves the slider to adjust the target value, the map quickly updates, forming a visual animation effect that helps users quickly capture the balance between different options.
Using this kind of animation, decision makers can visualize complex information and quickly evaluate which option is most appropriate.
Approximation of EPH
In IDM technology, the EPH must be approximated before the decision map is first displayed. These approximation methods depend on the convexity characteristics of EPH. For convexity problems, polyhedral sets are often used for approximation, while for general nonlinear problems an infinite but finite dominant cone can be used. These methods can provide decision makers with rapid and accurate visualization tools.
When EPH is approximated as a collection of polyhedra, we can describe this process with a system of linear inequalities.
Approximation and visualization under convex EPH
The polyhedron approximation for convex EPH can generate a large number of dual-objective slices, which can be calculated and displayed in a few seconds to form a decision map. Through such approximation, the complexity caused by too many layers is avoided while maintaining the clear presentation of information.
Search preference decisions
In IDM technology, the search preference decision is based on identifying a desired Pareto optimal target point. The decision map helps users clearly identify this goal on the computer screen and automatically find the corresponding Pareto optimal decision. This method not only improves the accuracy of decision-making, but also speeds up decision-making.
Future Development
With the development of IDM technology, more application scenarios will appear in the future, such as environmental protection, resource allocation, etc. The problems policymakers need to deal with are increasingly complex and the demands are growing. As data technology improves, dynamic decision maps will become more accurate and efficient. Can such a tool ultimately change our decision-making model and facilitate more efficient resource allocation?
In the face of diverse decision-making challenges, how to use technology to further improve decision-making efficiency will be the focus of future research.
