Batch Scheduling Model Of Heat Treatment Furnace Model Building And Its Optimization Algorithm

This paper studies batch scheduling model of heat treatment furnace, in the context of the actual production, considering the workpieces with dynamic time of arrival of the batch scheduling optimization problem, the innovations and the main work is:1. Aiming at the problem that workpieces can not be processed immediately after dynamic getting to the heat treatment workshop, and generate that there is waiting time for workpieces in the heat-treatment workshop in the process of actual production. The heat treatment workshop scheduling under workpieces with dynamic arrival time is consider, the batch scheduling model with expected waiting time of workpieces for the scheduling goal is built, and solved by making use of particle swarm optimization algorithm. In the process of solving, particle swarm algorithm of particle coding and batch of workpieces is came true according to the arrivals time of workpieces, the conclusion is achieved by simulation experiment:the shorter the processing time of workpieces, the less the expected waiting time of workpieces; under the circumstance of tending to be a small quantity of workpieces, waiting time expectation for large size workpieces is superior to small size workpieces, under the circumstance of tending to be a large quantity of workpieces, waiting time expectation for small size workpieces is superior to large size workpieces. Finally, in order to verify the validity of the algorithm, we make a comparison with ant colony algorithm, algorithm with FCFS and standard particle swarm algorithm. The simulation results show that the results of the particle swarm algorithm is the optimal.2. The initial moment global information incomplete single heat treatment furnace batch scheduling problem, target and weighted completion time. Because cannot arrive to solve dynamic and static global scheduling arrival time of the unknown batch scheduling problem, design the rolling time scheduling strategy based on prediction of time, under this strategy, complete step by step to obtain information with scheduling time domain of rolling workpieces. The mathematical model of the rolling batch scheduling time domain in punishing function with local scheduling time domain, using particle swarm algorithm of initial first come, first under the rules of the optimization scheduling results. The simulation results show that workpiece density arrived, weighted least arrival time rule scheduling results due to other conventional scheduling rules; Artifacts scattered arrived, first come, first processing is better than that of other conventional scheduling rules. Artifacts reach, scheduling cycle long, dense particle swarm algorithm scheduling relatively routine scheduling rules the optimization effect is obvious.