Abstract
In the realization process of discrete particle swarm optimization method for the problem, an optimal solving model is firstly designed according to the problem in NWBFFSSP, which minimizes the maximum time used in the flow shop. Besides, a forward iterative algorithm is proposed to calculate the target value while the permutation encoding is also applied. Finally, the discrete particle swarm optimization algorithm is utilized for global optimization. In the discrete particle swarm optimization algorithm, to avoid premature, an iterative greedy algorithm has been put forward to improve the local individual searching ability, and to realize the flexible flow shop scheduling in multi constraint conditions.
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