**AUTHORS:**Lin Wang, Jianhua Qu, Yucheng Jia

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**ABSTRACT:**
Permutation Flow Shop Scheduling Problem (PFSP) is a complex combinatorial optimization problem with strong engineering background. To solve the PFSP with makespan criterions, an immune particle swarm optimization (IPSO) algorithm was proposed. The initial solution of the algorithm is generated by the famous heuristic NEH algorithm, it was used to initialize the particle of global extreme values. Then we add a Dynamic Disturbance Term (DDT) in the velocity updating formulation of the particle, it used to prevent optimizing course from trapping the local minimum. Density and Immune Selection mechanism of Immune algorithm (IA) are used in the iterative process to select the optimal particle through the choice probability equation. The vaccination and memory operation to guide the global optimization process. At last, computational results show that the IPSO algorithm is effective robust and has a high performance.

**KEYWORDS:**
Permutation Flow Shop Scheduling, Particle Swarm Optimization Algorithm, Immune Algorithm, Makespan

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