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What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization

Zuzanna Osika, Jazmin Zatarain-Salazar, Diederik M. Roijers, Oliehoek Frans A., and Murukannaiah Pradeep K.. What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI), August 2023.

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Abstract

We present a review that unifies decision-support methods for exploring the solutions produced by multi-objective optimization (MOO) algorithms. As MOO is applied to solve diverse problems, ap- proaches for analyzing the trade-offs offered by MOO algorithms are scattered across fields. We provide an overview of the advances on this topic, including methods for visualization, mining the so- lution set, and uncertainty exploration as well as emerging research directions, including interactiv- ity, explainability, and ethics. We synthesize these methods drawing from different fields of research to build a unified approach, independent of the ap- plication. Our goals are to reduce the entry barrier for researchers and practitioners on using MOO al- gorithms and to provide novel research directions.

BibTeX Entry

@inproceedings{Osika23IJCAI,
    title = {What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization},
    author = {Osika, Zuzanna and Zatarain-Salazar, Jazmin and Roijers, Diederik M. and Oliehoek Frans A. and Murukannaiah Pradeep K.},
    booktitle = IJCAI23,
    keywords = {refereed},
    month = aug,
    year = {2023},
    keywords =  {refereed},
    abstract = {We present a review that unifies decision-support
        methods for exploring the solutions produced by
        multi-objective optimization (MOO) algorithms.
        As MOO is applied to solve diverse problems, ap-
        proaches for analyzing the trade-offs offered by
        MOO algorithms are scattered across fields. We
        provide an overview of the advances on this topic,
        including methods for visualization, mining the so-
        lution set, and uncertainty exploration as well as
        emerging research directions, including interactiv-
        ity, explainability, and ethics. We synthesize these
        methods drawing from different fields of research
        to build a unified approach, independent of the ap-
        plication. Our goals are to reduce the entry barrier
        for researchers and practitioners on using MOO al-
        gorithms and to provide novel research directions.},
}

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