摘要
为保证热轧生产调度计划的可行性,提高排程的效率,根据热轧生产模式和轧制计划的结构特点,提出了一种车辆路径问题(VRP)模型来建模轧制调度问题,发展了一种混合调度方法(SAMPSO算法)来解决这个问题。该方法利用修正粒子群优化算法的局部和全局搜索能力来寻找全局最优解,利用模拟退火方法来避免陷于局部最优。对某钢厂实际生产数据的仿真结果表明,所提出的模型和算法具有良好的适应性和可行性。
To guarantee the feasibility of hot rolling scheduling plan and improve the efficiency of arranging the scheduling, according to the characteristics of the hot rolling production mode and rolling plan structure, a VRP model was proposed to model the scheduling problem and a hybrid method （SAMPSO） was developed to solve the problem. In the hybrid method, the modified particle swarm optimization （MPSO） algorithm combines local search with global search to search the optimal results and simulated annealing （SA） employs certain probability to avoid becoming trapped in a local optimum. Computational results on practical production data are presented and show that the proposed model and algorithm are feasible and effective.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2006年第9期2484-2487,2562,共5页
Journal of System Simulation
基金
国家自然科学基金(60574063
60574049)
关键词
热轧生产调度
车辆路径问题
修正微粒群优化算法
模拟退火算法
hot rolling production scheduling
vehicle routing problem
particle swarm optimization
simulated annealing
