User preference extraction using dynamic query sliders in conjunction with UPS-EMO algorithm
Timo Aittokoski, Suvi Tarkkanen

TL;DR
This paper introduces a user-friendly method using dynamic query sliders within a graphical interface to extract decision maker preferences, guiding the UPS-EMO algorithm for more efficient multiobjective optimization with fewer evaluations.
Contribution
It presents a novel, intuitive approach for preference extraction in EMO, improving usability and efficiency over existing methods.
Findings
Reduces computational cost by focusing on preferred solution regions.
Enhances decision maker interaction through visual preference sliders.
Guides the UPS-EMO algorithm to generate targeted Pareto front segments.
Abstract
One drawback of evolutionary multiobjective optimization algorithms (EMOA) has traditionally been high computational cost to create an approximation of the Pareto front: number of required objective function evaluations usually grows high. On the other hand, for the decision maker (DM) it may be difficult to select one of the many produced solutions as the final one, especially in the case of more than two objectives. To overcome the above mentioned drawbacks number of EMOA's incorporating the decision makers preference information have been proposed. In this case, it is possible to save objective function evaluations by generating only the part of the front the DM is interested in, thus also narrowing down the pool of possible selections for the final solution. Unfortunately, most of the current EMO approaches utilizing preferences are not very intuitive to use, i.e. they may…
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Data Visualization and Analytics · Building Energy and Comfort Optimization
