@article {pub4440,
	title = {Surrogate Assisted Interactive Multiobjective Optimization in Energy System Design of Buildings},
	author = {Pouya Aghaei-Pour AND Tobias Rodemann AND Jussi Hakanen AND Kaisa Miettinen},
	year = {2021},
	month = {January},
	abstract = {In this paper, we develop a novel evolutionary interactive method called interactive K-RVEA, which is suitable for computationally expensive problems. We use surrogate models to replace
the original expensive objective functions in order to reduce the computation time. On the other hand, the decision maker should work with the solutions that are evaluated with the original
objective functions. Therefore, we propose a novel model management strategy to incorporate the decision maker{\textquoteright}s preferences to select some of the solutions for both updating the surrogate
models (in order to improve their accuracy) and to show them to the decision maker. Moreover, we solve a simulation-based computationally expensive optimization problem by finding an
optimal configuration for an energy system of a heterogeneous business building complex. We demonstrate how a decision maker can interact with the method and how the most preferred
solution is chosen. Finally, we compare our method with another interactive method, which does not have any model management strategy, and shows how our model management strategy
can help the algorithm to follow the decision maker{\textquoteright}s preferences.},
	publisher = {Springer, LNCS, LNAI, LNBI},
	journal = {Optimization and Engineering}
}