This is the result of my master thesis on Multi-Objective Optimization. This repository is more focused towards Pareto-based optimization rather than SIngle-Objective optimization with preference articulation. We focus on time-consuming optimization routines and, as a result we focus on model-based methods to allow for faster convergence times. This is relevant for Architectural Design Optimization, which depends on time-intensive simulations (e.g. minutes, hours or even days to complete a single simulation).
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Add Clustering techniques to base SBO workflow #26
Implement clustering methods to enhance solutions' diversity
Introduce mechanism to automatically sample a few solutions in case of the solutions divised by the optimiser were not diverse or not very revealing (e.g. when a single solution is returned, that makes linear regression methods worse...)
Implement clustering methods to enhance solutions' diversity Introduce mechanism to automatically sample a few solutions in case of the solutions divised by the optimiser were not diverse or not very revealing (e.g. when a single solution is returned, that makes linear regression methods worse...)