Multiobjective Artificial Immune Algorithm for Flexible Job Shop Scheduling Problem
نویسندگان
چکیده
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.
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A Novel Quantum Immune Algorithm for Multiobjective Flexible Job Shop Scheduling
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