Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Proceedings of the third international conference on Genetic algorithms
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 algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Outline for a Logical Theory of Adaptive Systems
Journal of the ACM (JACM)
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
New ideas in optimization
The ant colony optimization meta-heuristic
New ideas in optimization
Swarm intelligence
Evolutionary Computation: The Fossil Record
Evolutionary Computation: The Fossil Record
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
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Genetic Algorithms
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Representations for Genetic and Evolutionary Algorithms
Representations for Genetic and Evolutionary Algorithms
Adaptive Selection Methods for Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
How Genetic Algorithms Work: A Critical Look at Implicit Parallelism
Proceedings of the 3rd International Conference on Genetic Algorithms
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Intelligent behavior as an adaptation to the task environment
Intelligent behavior as an adaptation to the task environment
Knowledge-based solution to dynamic optimization problems using cultural algorithms
Knowledge-based solution to dynamic optimization problems using cultural algorithms
Telecommunication network design with parallel multi-objective evolutionary algorithms
LANC '03 Proceedings of the 2003 IFIP/ACM Latin America conference on Towards a Latin American agenda for network research
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper provides a brief introduction to evolutionary algorithms including some of their applications. Our discussion includes short descriptions of genetic algorithms, evolution strategies, evolutionary programming and genetic programming. Then, a few case studies involving applications of evolutionary algorithms in real-world problems are analyzed. In the final part of the paper, some of the current research directions in this area are provided.