Most optimization problems of practical significance are typically solved by highly
configurable parameterized algorithms. To achieve the best performance on a problem …

Metaheuristic and heuristic methods have many tunable parameters, and choosing their
values can increase their ability to deal with hard optimization problems. Automated …

The performance of an algorithm often critically depends on its parameter configuration.
While a variety of automated algorithm configuration methods have been proposed to …

Cutting-plane methods have enabled remarkable successes in integer programming over
the last few decades. State-of-the-art solvers integrate a myriad of cutting-plane techniques …

Algorithms often have tunable parameters that impact performance metrics such as runtime
and solution quality. For many algorithms used in practice, no parameter settings admit …

Tree search algorithms, such as branch-and-bound, are the most widely used tools for
solving combinatorial and non-convex problems. For example, they are the foremost method …

We present the first nontrivial procedure for configuring heuristic algorithms to maximize the
utility provided to their end users while also offering theoretical guarantees about …

We study the algorithm configuration (AC) problem, in which one seeks to find an optimal
parameter configuration of a given target algorithm in an automated way. Although this field …

Algorithm configuration methods optimize the performance of a parameterized heuristic
algorithm on a given distribution of problem instances. Recent work introduced an algorithm …

Over the last decade, research on automated parameter tuning, often referred to as
automatic algorithm configuration (AAC), has made significant progress. Although the …