Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Exact Solution of the Two-Dimensional Finite Bon Packing Problem
Management Science
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Hyper-heuristics: Learning To Combine Simple Heuristics In Bin-packing Problems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Hyper-heuristics and classifier systems for solving 2D-regular cutting stock problems
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Comparing two models to generate hyper-heuristics for the 2d-regular bin-packing problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Using Hyper-heuristics for the Dynamic Variable Ordering in Binary Constraint Satisfaction Problems
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Approximating multi-objective hyper-heuristics for solving 2D irregular cutting stock problems
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
A hyper-heuristic for solving one and two-dimensional bin packing problems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Automating the packing heuristic design process with genetic programming
Evolutionary Computation
Calibrating continuous multi-objective heuristics using mixture experiments
Journal of Heuristics
Hi-index | 0.00 |
The idea behind hyper-heuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. To be worthwhile, such combination should outperform the single heuristics. This paper presents a GA-based method that produces general hyper-heuristics that solve two-dimensional cutting stock problems. The GA uses a variable-length representation, which evolves combinations of condition-action rules producing hyper-heuristics after going through a learning process which includes training and testing phases. Such hyper-heuristics, when tested with a large set of benchmark problems, produce outstanding results (optimal and near-optimal) for most of the cases. The testbed is composed of problems used in other similar studies in the literature. Some additional instances of the testbed were randomly generated.