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2014 | 2 | 413--420
Tytuł artykułu

Hybrid GA-ACO Algorithm for a Model Parameters Identification Problem

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Języki publikacji
In this paper, a hybrid scheme using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) is introduced. In the hybrid GA-ACO, the GA is used to find feasible solutions to the considered optimization problem. Further ACO exploits the information gathered by GA. This process obtains a solution, which is at least as good as - but usually better than - the best solution devised by GA. To demonstrate the usefulness of the presented approach, the hybrid scheme is applied to parameter identification of E. coli MC4110 fed-batch fermentation process model. Moreover, a comparison with both the conventional GA and ACO is presented. The results show that the hybrid GA-ACO takes the advantages of both GA and ACO, thus enhancing the overall search ability and computational efficiency.(original abstract)
Opis fizyczny
  • Bulgarian Academy of Science
  • Polish Academy of Sciences
  • Bulgarian Academy of Science
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