Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables
<|reference_start|>Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables: In many real-world applications, the Pareto Set (PS) of a continuous multiobjective optimization problem can be a piecewise continuous manifold. A decision maker may want to find a solution set that approximates a small part of the PS and requires the solutions in this set share some similarities. This paper makes a first attempt to address this issue. We first develop a performance metric that considers both optimality and variable sharing. Then we design an algorithm for finding the model that minimizes the metric to meet the user's requirements. Experimental results illustrate that we can obtain a linear model that approximates the mapping from the preference vectors to solutions in a local area well.<|reference_end|>
@article{guo2024approximation,
    title={Approximation of a Pareto Set Segment Using a Linear Model with Sharing
  Variables},
    author={Ping Guo, Qingfu Zhang, Xi Lin},
    journal={arXiv preprint arXiv:2404.00251},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.00251},
    primaryClass={cs.NE}
}