A hybrid differential evolution algorithm integrated with an ant system and its application |
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Authors: | Chunping Hu Xuefeng Yan |
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Affiliation: | a Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, PR Chinab Department of Electric, Instrumentation and Control, Shanghai Nuclear Engineering Research and Design Institute, Shanghai 200233, PR China |
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Abstract: | A new hybrid differential evolution algorithm, in which an ant system is used to select the optimal base vector of mutation operation, named the ant system differential evolution (ASDE), is proposed. In ASDE, each dimension in the feasible solution space is divided into several subspaces evenly, and each subspace is marked with the same initial intensity of pheromone trails. The probability of choosing an individual as the base vector is influenced by the visibility and pheromone quantity of the individual. The trail of the selected base vector’s location subspaces will be reinforced with some pheromones, when the offspring is better than its parent. The experimental results show that the ASDE generally outperforms the other differential evolution algorithms for nine benchmark functions. Furthermore, the ASDE is applied to develop the global kinetic model for SO2 oxidation on the Cs-Rb-V catalyst, and satisfactory results are obtained. |
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Keywords: | Differential evolution Ant system Evolutionary computation Kinetic model |
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