Algorithm Selection for Combinatorial Search Problems: A Survey

Authors

  • Lars Kotthoff University College Cork

DOI:

https://doi.org/10.1609/aimag.v35i3.2460

Keywords:

problem solving, search, machine learning and discovery

Abstract

The algorithm selection problem is concerned with selecting the best algorithm to solve a given problem instance on a case-by-case basis. It has become especially relevant in the last decade, with researchers increasingly investigating how to identify the most suitable existing algorithm for solving a problem instance 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 article contrasts and compares different methods for solving the problem as well as ways of using these solutions.

Author Biography

Lars Kotthoff, University College Cork

Researcher at Cork Constraint Computation Centre
AI Magazine Fall Issue

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Published

2014-09-19

How to Cite

Kotthoff, L. (2014). Algorithm Selection for Combinatorial Search Problems: A Survey. AI Magazine, 35(3), 48-60. https://doi.org/10.1609/aimag.v35i3.2460

Issue

Vol. 35 No. 3: Fall 2014

Section

Articles

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