混合人工蜂群算法在混流装配线排序中的应用

Application of hybrid artificial bee colony algorithm in mixed assembly lines sequencing

为更好地解决混流汽车装配线排序问题,建立了以最小化总调整时间和最小化超载时间与空闲时间为优化目标的典型混流装配线排序数学模型,提出一种求解该模型的混合人工蜂群算法。针对标准人工蜂群算法不能解决离散问题的缺陷,引入禁忌搜索算法重新设计了蜂群的邻域搜索算法,设置了算法邻域搜索的动态参数,设计了禁忌搜索算法在人工蜂群算法中的嵌入策略;为保证算法的全局收敛性,采用基于跟随蜂的精英保留策略,给出了侦查蜂和跟随蜂的食物源更新方法。通过比较混合人工蜂群算法与遗传算法和标准人工蜂群算法对不同规模算例的计算结果,验证了所提算法在求解混流装配线排序问题中的优越性。

To solve the sequencing problem of mixed model automobile assembly line, a hybrid Artificial Bee Colony （ABC） algorithm was proposed with the objectives of minimizing total setup time, utility time and idle time. To o vercome the defect that ABC could not solve discrete problem, the Tabu Search （TS） algorithm was introduced to design the neighborhood TS algorithm of bee colony. The dynamic parameter was set for neighborhood searching range. The embedded strategy of TS in ABC was designed. An elitism strategy of follow bees was adopted to ensure the global convergence. The scouts and onlookers updating method were presented. Several different scale examples and algorithm comparison was presented to prove the effectiveness and superiority of proposed algorithm for solving assembly sequencing problem.