求解混流装配线调度的疫苗共生克隆选择算法

针对混流装配线的多目标调度优化问题,提出了一种疫苗协同进化的多目标免疫克隆选择优化算法.设计了疫苗种群及其相关操作,使其跟抗体种群相互影响并协同进化,提高了算法的性能;针对调度优化问题的离散性,选择同时从抗体的基因型和表现型评价抗体亲和度;依据抗体质量和进化代数,设计了自适应变异率;在每次迭代过程中,通过多次局部寻优加快算法收敛速度.最后通过两组实例仿真,与另3种多目标优化算法进行比较,结果证明该算法可得到更好的计算结果.

A Vaccine-Symbiosis Clonal Selection Algorithm for Mixed-Model Scheduling on Assembly Lines

A Multi-Objective Vaccine Co-evolution Clonal Selection Algorithm has been proposed to solve the sequencing problem of MMAL. Vaccine population and antibody population have come up. Relative operators of vaccine population are designed to affect and co-evolve with the antibody population. In the light of the discrete feature of the sequencing problem, the antibody affinity is evaluated from the phenotype as well as the genotype; The rate of mutation operator is designed to be self-adaptive according to the quality of the antibody and the generations; The multiple local optimizations have been executed to improve the convergence rate of the algorithm. The results of the two series of experiments compared with other algorithms show the efficiency and superiority of the proposed algorithm.