Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
On the run-time behaviour of stochastic local search algorithms for SAT
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Local Search Algorithms for SAT: An Empirical Evaluation
Journal of Automated Reasoning
Using genetic programming to learn and improve control knowledge
Artificial Intelligence
Evolutionary algorithms for the satisfiability problem
Evolutionary Computation
Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Automated discovery of composite SAT variable-selection heuristics
Eighteenth national conference on Artificial intelligence
A Study on the use of "self-generation'' in memetic algorithms
Natural Computing: an international journal
GASAT: a genetic local search algorithm for the satisfiability problem
Evolutionary Computation
Deconstructing planning as satisfiability
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Adaptive problem-solving for large-scale scheduling problems: a case study
Journal of Artificial Intelligence Research
Algorithm portfolio design: theory vs. practice
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Evolving bin packing heuristics with genetic programming
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Evolving reusable 3d packing heuristics with genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolving human-competitive reusable 2D strip packing heuristics
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Towards the decathlon challenge of search heuristics
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Massively parallel evolution of SAT heuristics
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A gender-based genetic algorithm for the automatic configuration of algorithms
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Incremental evolution of local search heuristics
Proceedings of the 12th annual conference on Genetic and evolutionary computation
ISAC --Instance-Specific Algorithm Configuration
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Autonomous operator management for evolutionary algorithms
Journal of Heuristics
Generating meta-heuristic optimization code using ADATE
Journal of Heuristics
Modern continuous optimization algorithms for tuning real and integer algorithm parameters
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
A genetic programming hyper-heuristic approach for evolving 2-D strip packing heuristics
IEEE Transactions on Evolutionary Computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Automating the packing heuristic design process with genetic programming
Evolutionary Computation
Dynamic scoring functions with variable expressions: new SLS methods for solving SAT
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Variable and value ordering decision matrix hyper-heuristics: a local improvement approach
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Matrix analysis of genetic programming mutation
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
Estimating meme fitness in adaptive memetic algorithms for combinatorial problems
Evolutionary Computation
Hyper-heuristics with low level parameter adaptation
Evolutionary Computation
Genetic Programming and Evolvable Machines
International Journal of Applied Metaheuristic Computing
A genetic programming approach to hyper-heuristic feature selection
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
Generation of VNS components with grammatical evolution for vehicle routing
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
A new hyper-heuristic as a general problem solver: an implementation in HyFlex
Journal of Scheduling
Using automatic programming to generate state-of-the-art algorithms for random 3-SAT
Journal of Heuristics
Genetic programming for evolving due-date assignment models in job shop environments
Evolutionary Computation
Contrasting meta-learning and hyper-heuristic research: the role of evolutionary algorithms
Genetic Programming and Evolvable Machines
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The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.