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
GENITOR II.: a distributed genetic algorithm
Journal of Experimental & Theoretical Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, GE
Genetic Algorithms
Case-Based Initialization of Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A Comparison of Dominance Mechanisms and Simple Mutation on Non-stationary Problems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Polygenic Inheritance - A Haploid Scheme that Can Outperform Diploidy
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A memory-based colonization scheme for particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Mechanisms for evolutionary reincarnation
ACAL'07 Proceedings of the 3rd Australian conference on Progress in artificial life
An external partial permutations memory for ant colony optimization
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Registrar: a complete-memory operator to enhance performance of genetic algorithms
Journal of Global Optimization
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This paper introduces a novel genetic algorithm strategy based on the reuse of chromosomes from previous generations in the creation of offspring individuals. A number of chromosomes of above-average quality, that are not utilized for recombination in the current generation, are inserted into a library called the chromosome library. The main motivation behind the chromosome reuse strategy is to trace some of the untested search directions in the recombination of potentially promising solutions. In the recombination process, chromosomes of current population are combined with the ones in the chromosome library to form a population from which offspring individuals are to be created. Chromosome library is partially updated at the end of each generation and its size is limited by a maximum value. The proposed algorithm is applied to the solution of hard numerical and combinatorial optimization problems. It outperforms the conventional genetic algorithms in all trials.