There exists a proliferation of different approaches to using portfolios and algorithm selection to make solving combinatorial search and optimisation problems more efficient, as surveyed in the previous chapter. In this chapter, we take a look at a detailed case study that leverages transformations between problem representations to make portfolios more effective, followed by extensions to the state of the art that make algorithm selection more robust in practice.
CITATION STYLE
Hurley, B., Kotthoff, L., Malitsky, Y., Mehta, D., & O’Sullivan, B. (2016). Advanced portfolio techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10101 LNCS, pp. 191–225). Springer Verlag. https://doi.org/10.1007/978-3-319-50137-6_8
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