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Therefore, this paper proposes an effective optimization method, based on the novel Multi Population Pattern Searching (MuPPetS) Algorithm, to solve optimization problems characterized with very large solution space.
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This study aims to develop a multi-objective multi-population biased random-key genetic algorithm for the three-dimensional single container loading problem.
Multi-population, multi-phenotype views also have found success before in integrative visualization systems [ 17] -[ 19].
The lack of attention on these challenging issues within multi-population methods hinders the development of multi-population based algorithms in dynamic environments.
Coelho [ 14] combines the multi-population of aiNet and the biclustering techniques, and proposes MOM-aiNet (Multi-Objective Multi-population Artificial Immune Network) algorithm to mining biclusters.
We implemented an extended multi-population genetic algorithm (EMPGA), where subpopulations apply different evolutionary strategies.
We proposed a cooperative particle swarm optimization model with cooperative multi-population.
This paper develops an effective novel hybrid multi-population genetic algorithm.
Multi-population algorithms have been widely used for solving the real-world problems.
In addition, the comparison with other multi-population GA shows that competition between subpopulations improved the quality of solution.
In particular, the proposed genetic algorithm applied multi-population strategy and fuzzy logic controller (FLC) to improve efficiency and effectiveness.
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