Algorithm Selection for Combinatorial Search Problems: A Survey

TLDR

Algorithm selection aims to choose the best algorithm for each problem instance, a task that has gained prominence over the past decade as researchers focus on identifying suitable existing algorithms rather than creating new ones. The survey reviews contributions to algorithm selection for combinatorial search problems, highlighting significant performance gains. The authors systematically classify and compare algorithm selection approaches for combinatorial search, organizing the literature by practical criteria and contrasting methods for solving and applying the problem.

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 analyzes 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.