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- W4361792241 abstract "The traditional Genetic Algorithm is not only easy to fall into the local optimal solution, but also has poor stability. In response to this problem, I. Harvey proposed a Microbial Genetic Algorithm. Using the idea of microbial inheritance, the process of selection and crossover in the classical genetic algorithm is replaced by means of confrontation and infection. This algorithm can retain better parent population, and save those genes. However, this algorithm works well for small populations, and because only one new offspring is generated per confrontation, the efficiency is the problem. Aiming at this problem, an Improved Microbial Genetic Algorithm (IMGA) is proposed, which transforms random confrontation into ordered group confrontation with roulette selection algorithm. The simulation results of the TSP problem show that the new algorithm is suitable for large populations and the efficiency is also improved. Both in terms of time efficiency and the results of the optimal solution, IMGA is better than GA and MGA." @default.
- W4361792241 created "2023-04-05" @default.
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- W4361792241 date "2022-12-01" @default.
- W4361792241 modified "2023-09-27" @default.
- W4361792241 title "IMGA: Improved Microbial Genetic Algorithm" @default.
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- W4361792241 doi "https://doi.org/10.1109/qrs-c57518.2022.00036" @default.
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