Introduction to algorithms
Uniform crossover in genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
A compiling genetic programming system that directly manipulates the machine code
Advances in genetic programming
Evolving programmers: the co-evolution of intelligent recombination operators
Advances in genetic programming
Two self-adaptive crossover operators for genetic programming
Advances in genetic programming
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Self-adaptation in evolving systems
Artificial Life
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Evolving Teams of Predictors with Linear Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming and Autoconstructive Evolution with the Push Programming Language
Genetic Programming and Evolvable Machines
Explicit Control of Diversity and Effective Variation Distance in Linear Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Fitness landscape analysis and memetic algorithms for the quadratic assignment problem
IEEE Transactions on Evolutionary Computation
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
A-Brain: the multiple problems solver
Proceedings of the 2006 ACM symposium on Applied computing
Evolving evolutionary algorithms using evolutionary algorithms
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
What else is the evolution of PSO telling us?
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
A-Brain: a general system for solving data analysis problems
Journal of Experimental & Theoretical Artificial Intelligence
Evolution of Search Algorithms Using Graph Structured Program Evolution
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
There Is a Free Lunch for Hyper-Heuristics, Genetic Programming and Computer Scientists
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Design & Implementation of Parallel Linear GP for the IBM Cell Processor
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolutionary design of Evolutionary Algorithms
Genetic Programming and Evolvable Machines
Automatic algorithm configuration based on local search
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
SATenstein: automatically building local search SAT solvers from components
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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
Cost-benefit investigation of a genetic-programming hyperheuristic
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Open issues in genetic programming
Genetic Programming and Evolvable Machines
ISAC --Instance-Specific Algorithm Configuration
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Modern continuous optimization algorithms for tuning real and integer algorithm parameters
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Designing pheromone update strategies with strongly typed genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Evolving fitness functions for mating selection
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Evolving the structure of the particle swarm optimization algorithms
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Evolving evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
The automatic generation of mutation operators for genetic algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
An adaptive evolutionary approach for real-time vehicle routing and dispatching
Computers and Operations Research
Automatic (offline) configuration of algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
HH-evolver: a system for domain-specific, hyper-heuristic evolution
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Evolving black-box search algorithms employing genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Contrasting meta-learning and hyper-heuristic research: the role of evolutionary algorithms
Genetic Programming and Evolvable Machines
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A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.