Nonstationary function optimization using genetic algorithm with dominance and diploidy
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Genetic Algorithms for Tracking Changing Environments
Proceedings of the 5th International Conference on Genetic Algorithms
A Comparative Study of Steady State and Generational Genetic Algorithms
Selected Papers from AISB Workshop on Evolutionary Computing
Memory-based immigrants for genetic algorithms in dynamic environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Genetic algorithms with memory-and elitism-based immigrants in dynamic environments
Evolutionary Computation
Ant colony optimization with immigrants schemes in dynamic environments
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Particle swarm optimization with composite particles in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Perspectives in dynamic optimization evolutionary algorithm
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Memory-based CHC algorithms for the dynamic traveling salesman problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
CHC-based algorithms for the dynamic traveling salesman problem
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Fuzzy genetic sharing for dynamic optimization
International Journal of Automation and Computing
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Addressing dynamic optimization problems has been a challenging task for the genetic algorithm community. Over the years, several approaches have been developed into genetic algorithms to enhance their performance in dynamic environments. One major approach is to maintain the diversity of the population, e.g., via random immigrants. This paper proposes an elitism-based immigrants scheme for genetic algorithms in dynamic environments. In the scheme, the elite from previous generation is used as the base to create immigrants via mutation to replace the worst individuals in the current population. This way, the introduced immigrants are more adapted to the changing environment. This paper also proposes a hybrid scheme that combines the elitism-based immigrants scheme with traditional random immigrants scheme to deal with significant changes. The experimental results show that the proposed elitism-based and hybrid immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.