  The Algorithm Selection Problem is concerned with selecting the best
algorithm to solve a given problem on a case-by-case basis. It has become
especially relevant in the last decade, as researchers are increasingly
investigating how to identify the most suitable existing algorithm for solving
a problem instead of developing new algorithms. This survey presents an
overview of this work focusing on the contributions made in the area of
combinatorial search problems, where Algorithm Selection techniques have
achieved significant performance improvements. We unify and organise the vast
literature according to criteria that determine Algorithm Selection systems in
practice. The comprehensive classification of approaches identifies and
analyses the different directions from which Algorithm Selection has been
approached. This paper contrasts and compares different methods for solving the
problem as well as ways of using these solutions. It closes by identifying
directions of current and future research.
