First, a multi-objective immune genetic algorithm integrating immune algorithm and genetic algorithm for flexible job shop scheduling is designed. Second, Markov chain is used to analyze quantitatively its convergence. Third, a simulation experiment of the flexible job shop scheduling is carried out. Running results show that the proposed algorithm can converge to the Pareto frontier quickly and distribute evenly along the Pareto frontier. © 2006 International Federation for Information Processing.
CITATION STYLE
Wu, X. L., Sun, S. D., Niu, G. G., & Zhai, Y. N. (2006). The performance analysis of a multi-objective immune genetic Algorithm for flexible job shop scheduling. In IFIP International Federation for Information Processing (Vol. 207, pp. 914–919). https://doi.org/10.1007/0-387-34403-9_128
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