利用精英策略ST-ACO算法对UA-FLP的优化求解

Optimization of unequal area facility layout problem based on ST-ACO with elitist strategy

针对制造业中常见的不等面积设施布局优化问题(UA-FLP),提出了一种精英策略蚁群优化算法(ACO)。该算法的主要特点是采用基于切片树(ST)的编码方法,将解分成三部分,即一只蚂蚁代表一个解,它有三部分的信息素;然后结合启发式信息,进行更新寻优,得到最小的物流费用;同时采用比较新颖的边界曲线(BC)回溯方法求出最小物流费用所对应的设施布局尺寸,并确定设施之间最优的输入、输出点(I、O)位置;最后,通过算例对比证明了该方法在解决中小规模实际问题中的有效性及相比于某些现存方法的优越性。

For the unequal area facility layout problem in manufacturing, an ACO algorithm with elitist strategy is put forward. This algorithm adopts the coding method based on slicing tree to divide the solution into three parts ,which stand for three types of pheromone of an ant, then combined with heuristic information to find the optimal solution that minimizes the total material flow cost. At the same time, a new method called bounding curve backtracking is used to visualize the facility layout corresponding to the optimal solution, and the input/output point position of each facility can also be confirmed during the search. Finally, several experiments are performed to prove the validity of this algorithm in solving small and medium problems as well as its superiority to some other existing methods.