期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2012
卷号：5
期号：3
出版社：SERSC
摘要：Flexible Job shop scheduling is very important in production management and combinatorial optimization. It is NP-hard problem and consists of two sub-problems: sequencing and assignment. Multiobjective Flexible Job-Shop Scheduling Problems (MFJSSP) is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. In this paper a Multiobjective Artificial Immune Algorithm (MAIA) for FJSSP is presented. The proposed algorithm increases the speed of convergence and diversity of population. Kacem and Bradimart data are used to evaluate the effectiveness of MAIA. The experimental results show a better performance in comparison to other approaches
