Research on Dynamic Flexible Job Shop Scheduling Problem Based on Dynamic Interaction Layer

doi:10.16182/j.issn1004731x.joss.20-FZ0401

Abstract

Abstract: In order to quickly response to the unforeseen circumstances in flexible job shop, a dynamic flexible job shop scheduling model is constructed, which takes the overall production time and the completion time of emergency orders as the optimization objectives. For the model, a dynamic interaction layer (DIL) model, which has a better performance on DFJSP, is proposed to replace the scroll window. Particle swarm genetic hybrid algorithm (PSGA) is designed to combine the particle swarm optimization algorithm with the genetic algorithm to enhance the ability of local search. Aiming at the unexpected urgent orders in flexible job shop, DIL and PSGA are combined to solve the dynamic scheduling problem. The simulation experiments verify DIL's ability to handle urgent orders and the effectiveness of PSGA.

Key words: flexible job shop scheduling problem, particle swarm genetic hybrid algorithm, dynamic interaction layer, dynamic scheduling

CLC Number:

TP278

Zhang Xiang, Wang Yan, Ji Zhicheng. Research on Dynamic Flexible Job Shop Scheduling Problem Based on Dynamic Interaction Layer[J]. Journal of System Simulation, 2020, 32(11): 2129-2137.

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