中文摘要：

为优化直角坐标码垛机器人码垛次序,节省码垛时间,针对空间中不同类型的物料箱分散堆放与随机选取堆垛位置对拆垛堆垛作业的影响,以拆垛顺序、堆垛顺序、堆垛区域为决策变量,以整个拆垛和堆垛过程总路径最短为目标,构建了物料箱选择与堆垛位置分配的数学模型。将模拟退火算法与遗传算法进行结合改进,设计了基于自适应模拟退火遗传算法的双层启发式算法,对模型进行同步优化,并通过104个物料箱的算例仿真,得到了一组最优的码垛次序。仿真结果表明,与一组随机的码垛次序相比,对物料箱进行选择并对堆垛位置进行分配可以有效缩短工作路径,节省工作时间,模型与算法可行有效。

英文摘要：

In order to optimize the robot stacking sequence of rectangular axes and save stacking time,avoid influences like different kinds of material boxes, random stacking and random position choice on piling work, this paper builds up a mathematical model involving material boxes choice and stacking position distribution and designs a two - level heuristic algorithm based on an adaptively simulated annealing genetic algorithm to solve the problems. We take unstacking sequence, stacking sequence,and stacking area as decisive variables and aim to make the shortest route of stacking and unstacking process. This paper makes simultaneous optimization on the model and gets a set ofoptimal stacking sequence according to the simulation of 104 material boxes. The simulation results show that, compared with a set of random stacking sequence, material boxes5 choice and stacking position distribution can effectively cut down working route and working t ime,which means that the model and algorithm are feasible and effective.