A two-step ACO-PSO approach to optimize flexible jobshop scheduling of air compressor based on Petri net model

A mathematical model of operation on air compressors is set up in order to improve the efficiency of manufacturing key parts of air compressors. Moreover, a timed Petri net is used to model discrete events in scheduling of flexible production lines. The timed Petri net can manage the time, resource and cost of technics process synthetically when the process is affected by resource restrictions and sudden incidents. A two-step hierarchically evolutionary optimization approach for flexible jobshop scheduling of the air compressor is proposed based on the above timed Petri net model. The process route of jobs is optimized by a an Ant Colony Optimization (ACO)Particle approach. On the basis of the optimal process route, an Swarm Optimization (PSO) approach is also used to optimize the sequence of operations processed on a same machine. The effectiveness and practicability of the algorithm is testified.