自动导引车(automatic guided vehicle，AGV）逐渐成为车间生产工件运输的重要工具，这给车间生产调度带来了新的问题，如AGV分配、AGV电量约束、AGV数量约束等。针对AGV运输的绿色作业车间调度问题，在考虑AGV能耗、电量及充电的情况下，提出了一种最小完工时间和最小能耗的多目标作业车间调度优化模型，并设计了一种改进遗传算法进行求解，该算法采用等长的工件分配和AGV分配两段式编码方式，设计了工件和AGV相应的遗传操作算子和局部搜索策略，针对AGV电量及充电约束设计了解码机制。最后通过FT06用例的实验仿真，并采用极差和方差的方法分析了AGV数量、AGV电量对优化目标的影响，仿真实验验证了所提模型和算法的有效性。

Automatic guided vehicle (AGV) has become an important transportation tool in job shop, which brings new problems for job shop scheduling, such as AGV assigned, AGV power constraint, AGV quantity constraint and so on. Aiming to green scheduling problem of job shop considering AGVs charging, the multi-objective job shop scheduling optimization model with makespan and energy consumption was established considering the AGV power and AGV charging, and the improved genetic algorithm is devised to solve this model. In the algorithm, the two-segment chromosome coding of equal length job assignment and AGV allocation was using, the local search strategy and corresponding GA operators for job and AGV code segment were adopted, the decoding mechanism considering AGV power and charging constraints was designed. Finally, through the orthogonal experimental simulation of ft06 case using the method of range and variance, the influence of AGV quantity and AGV power on the optimization was analyzed. The model and algorithm were verified by simulation.

TP278；TP18

国家自然科学基金联合基金资助项目(U1904167)；河南省高校科技创新团队(21IRTSTHN018)；河南省高等学校重点科研项目计划(19A460034)