Joint optimization of Picking Operation Based on Nested Ant Colony Algorithm
Aiming at the problem of low efficiency of systematic order batching and picking path step-by-step picking in the pro-cess of picking operation of logistics warehousing center,a joint picking strategy based on nested ant colony batching and path optimization is proposed.Firstly,a joint optimization model of order batch and picking route with the goal of minimizing the total path is established;Then,considering the complexity of double optimization,a nested ant colony algorithm is designed to solve the model.The order batching model is used as the benchmark to continuously optimize the order batch results,obtaining the op-timal batch collection order.Subsequently,The nested ant colony algorithm is applied to realize the picking path optimization.In order to verify the effectiveness of the algorithm on random orders,43 order studies with both shelf area and ground pile area goods from a certain day between 17:00 and 18:00 were sampled for simulation experiments.Compared with the traditional order batching and picking path step-by-step picking strategy,the random order picking path based on the nested ant colony algorithm joint optimization model of picking operation is shorter,the picking time is less.After joint optimization,the total picking dis-tance is shortened by 170 m.The joint optimization model of picking operation based on nested ant colony algorithm and its solu-tion algorithm can effectively adress the problem of joint optimization of order batching and picking path,and provide a basis for the optimization of the picking system in the distribution center.
nested ant colony algorithmorder batchingdynamic pickingjoint optimization
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