Aug 1, 2024 · In this study, we propose to exploit the well-known Lower Confidence Bound acquisition function in Bayesian optimization, to interactively ...
Jul 18, 2024 · An approach to ensure a diverse. Pareto front with numerous options involves employing multi- objective optimization algorithms specifically ...
A survey on kriging-based infill algorithms for multiobjective simulation optimization · Engineering, Computer Science. Computers & Operations Research · 2020.
Aug 6, 2024 · Lower confidence bound for preference selection in interactive multi-objective optimization ; Publication type: Conference Paper (Proceedings ...
Lower Confidence Bound for Preference Selection in Interactive Multi-Objective Optimization. A Heidari, S Rojas Gonzalez, T Dhaene, I Couckuyt. Proceedings of ...
We address this issue by using a multi-objective Bayesian optimization algorithm and allowing the DM to select a preferred solution from a predicted continuous ...
The lower confidence bound (LCB) [33] is a powerful infill criterion that combines the uncertainty information with the predicted objective values for tackling ...
Typically, this solution is found by solving a single-objective optimization problem that generates either an efficient point or, at worst, a feasible point.
Missing: Lower | Show results with:Lower
Sep 10, 2024 · We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting.
Jan 13, 2022 · These bounds form a so-called preferred range. A lower bound is the preferred minimum value, whereas an upper bound is the preferred maximum ...