摘要
提出了一种基于成本的Flowshop调度问题的数学模型。该模型考虑影响调度决策的各种成本,如生产切换费用、机器空闲造成的损失、工件提前或拖期完工造成的损失等。在此基础上提出了一种基于人工免疫算法和模拟退火的混合智能算法,该算法利用人工免疫算法的全局搜索能力以及模拟退火的局部搜索能力来搜索全局最优解。仿真实验表明了模型的可行性和算法的有效性。
A cost-driven model of flowshop scheduling problem （FSP） is established. The cost model is developed in terms of a combination of multi-dimensional costs generated from product transitions, revenue loss, and earliness/tardiness penalty, etc. On the basis of the model, a new algorithm which combines the artificial immune algorithm and simulated annealing with strong local search ability is put forward. This algorithm can search global optimization by use of strong global search ability of artificial immune algorithm with strong local search ability of simulated annealing. The experimental simulation tests prove the reliability of the model and the effectiveness the algorithm.
出处
《山东交通学院学报》
CAS
2011年第4期76-81,86,共7页
Journal of Shandong Jiaotong University
基金
山东省自然科学基金资助项目(ZR2010FQ009)
