Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Computers and Operations Research
Memetic algorithms: a short introduction
New ideas in optimization
A Hyperheuristic Approach to Scheduling a Sales Summit
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Hierarchical Iterated Local Search for the Quadratic Assignment Problem
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
A hybrid TP+PLS algorithm for bi-objective flow-shop scheduling problems
Computers and Operations Research
An incremental ant colony algorithm with local search for continuous optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Automatic configuration of state-of-the-art multi-objective optimizers using the TP+PLS framework
Proceedings of the 13th annual conference on Genetic and evolutionary computation
HyFlex: a benchmark framework for cross-domain heuristic search
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
Hyper-heuristics and cross-domain optimization
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
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In this work, we present our submission for the Cross-domain Heuristic Search Challenge 2011. We implemented a stochastic local search algorithm that consists of several algorithm schemata that have been offline-tuned on four sample problem domains. The schemata are based on all families of low-level heuristics available in the framework used in the competition with the exception of crossover heuristics. Our algorithm goes through an initial phase that filters dominated low-level heuristics, followed by an algorithm schemata selection implemented in a race. The winning schema is run for the remaining computation time. Our algorithm ranked seventh in the competition results. In this paper, we present the results obtained after a more careful tuning, and a different combination of algorithm schemata included in the final algorithm design. This improved version would rank fourth in the competition.