5 citations · 6 across the 3 of their papers we have counts for
4 papers
R-MBO: A Multi-surrogate Approach for Preference Incorporation in Multi-objective Bayesian Optimisation
Tinkle Chugh
Many real-world multi-objective optimisation problems rely on computationally expensive function evaluations. Multi-objective Bayesian optimisation (BO) can be used to alleviate th…
Wind Farm Layout Optimisation using Set Based Multi-objective Bayesian Optimisation
Tinkle Chugh, Endi Ymeraj
Wind energy is one of the cleanest renewable electricity sources and can help in addressing the challenge of climate change. One of the drawbacks of wind-generated energy is the la…
What Makes an Effective Scalarising Function for Multi-Objective Bayesian Optimisation?
Clym Stock-Williams, Tinkle Chugh, Alma Rahat +1
Performing multi-objective Bayesian optimisation by scalarising the objectives avoids the computation of expensive multi-dimensional integral-based acquisition functions, instead o…
Scalarizing Functions in Bayesian Multiobjective Optimization
Tinkle Chugh
Scalarizing functions have been widely used to convert a multiobjective optimization problem into a single objective optimization problem. However, their use in solving (computatio…