An introduction to genetic algorithms
An introduction to genetic algorithms
The vehicle routing problem
Using Experimental Design to Find Effective Parameter Settings for Heuristics
Journal of Heuristics
A Racing Algorithm for Configuring Metaheuristics
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Ant Colony Optimization
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
An effective hybrid algorithm for university course timetabling
Journal of Scheduling
Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search
Operations Research
Improvement strategies for the F-Race algorithm: sampling design and iterative refinement
HM'07 Proceedings of the 4th international conference on Hybrid metaheuristics
S-Race: a multi-objective racing algorithm
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Automatic (offline) configuration of algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
The consultation timetabling problem at Danish high schools
Journal of Heuristics
A beginner's guide to tuning methods
Applied Soft Computing
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Stochastic local search (SLS) methods like evolutionary algorithms, ant colony optimisation or iterated local search receive an ever increasing attention for the solution of highly application relevant optimisation problems. Despite their noteworthy successes, several issues still hinder their even wider spread. One central issue is the configuration and parameterisation of SLS methods, which is known to be a time- and personal-intensive process. Recently, several attempts have been made to automate the tuning of SLS algorithms. One of the most promising directions is the usage of the racing methodology, which is a statistical method for selecting promising candidate configurations. We present results of a study on the application of this methodology to the tuning of a complex SLS method for an industrial vehicle scheduling and routing problem, and compare the performance of two racing methods.