Abstract
Solutions that provide a balance between different objective values in multi-objective optimization can be identified by assessing the curvature of the Pareto front. We analyze how methods based on angles have been utilized in the past for this task and propose a new angle-based measure—angle utility—that ranks points of the Pareto front irrespective of its shape or the number of objectives. An algorithm for finding angle utility optima is presented and a computational study shows that this algorithm is successful in identifying angle utility optima.
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Braun, M., Shukla, P., Schmeck, H. (2017). Angle-Based Preference Models in Multi-objective Optimization. In: Trautmann, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2017. Lecture Notes in Computer Science(), vol 10173. Springer, Cham. https://doi.org/10.1007/978-3-319-54157-0_7
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DOI: https://doi.org/10.1007/978-3-319-54157-0_7
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