Abstract
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.
This project is by the National High-Tech. R&D Program for CIMS, China under the grant No 2003AA411110 and by Doctoral Fund of Ministry of Education of China under the grant No 20040699025
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© 2006 International Federation for Information Processing
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Wu, X., Sun, S., Niu, G., Zhai, Y. (2006). The Performance Analysis of a Multi-Objective Immune Genetic Algorithm for Flexible Job Shop Scheduling. In: Wang, K., Kovacs, G.L., Wozny, M., Fang, M. (eds) Knowledge Enterprise: Intelligent Strategies in Product Design, Manufacturing, and Management. PROLAMAT 2006. IFIP International Federation for Information Processing, vol 207. Springer, Boston, MA . https://doi.org/10.1007/0-387-34403-9_128
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DOI: https://doi.org/10.1007/0-387-34403-9_128
Publisher Name: Springer, Boston, MA
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