基于结构式译码遗传算法平衡多人共站装配线

Genetic algorithm based on structural decoding algorithm for Multi-Manned Assembly Line Balancing Problem

针对多人共站装配线第二类平衡问题,以最小化装配线节拍为主要目标,最小化平行操作工人数为第一辅助目标,最小化工人负荷标准差为第二辅助目标构建数学模型,在此基础上,构建结构式译码遗传算法,其中特别设计了两阶段结构式译码算法,在第一阶段,求解给定作业序列在单人工作站条件下的最优分配方案,第二阶段将方案中的工作站进行合并,以使节拍最小化。通过算例验证算法的有效性和可行性。

To solve Multi-Manned Assembly Line Balancing Problem of type Ⅱ（MM-ALBP Ⅱ）, a mathematical model, aiming to minimize the cycle time firstly, the number of parallel operators secondly and the workload variances between operators third- ly, is constructed. A genetic algorithm is developed. Especially in the decoding stage a two-phase structural decoding algorithm is designed, which first optimally assigns the tasks to the sequential stations, and then the cycle time is further decreased by merging stations. The computational results demonstrate the feasibility and outstanding character of the proposed algorithm.