基于免疫算法的多目标柔性job-shop调度研究

建立了多目标柔性job-shop调度模型;然后提出了带有保优机制免疫算法,利用免疫记忆、接种疫苗等机制,在算法中保留并充分利用每代最优抗体和局部最优基因,使算法加快收敛;针对这类调度的柔性,提出基于工序设备双层抗体编码方案和基于设备能力空间的解码方案;采用多目标分级评价方法同时对时间、设备和成本等多目标进行评价和优化.最后,用Benchm ark标准问题的仿真和西安航空发动机(集团)有限公司的调度实例验证了算法、策略和调度模型的有效性和优越性.

Multi-objective flexible job-shop scheduling based on immune algorithm

A model of multi-objective flexible job-shop scheduling (MOFJS) is built.An immune algorithm with excellence holding is put forward.To accelerate the convergence of the algorithm,the best antibodies and the local best genes in the algorithm are held and utilized by using mechanisms of immunity memory and immunity vaccine in every generation.Focusing on the flexibility of MOFJS,a double layer antibody coding project based on working procedure and equipments,and a decoding project based on equipment capability space are proposed.Using the multi-objective ranking evaluation technique the evaluation and optimization are carried out to several objects,such as time,equipment and cost.The superiorities and validities of the algorithm,strategy and model are demonstrated by the simulation of Benchmark standard scheduling problems and a scheduling example of the Xi'an Aviation Engine Corporation in China.