Components and Parts Picking Cluster Model Based on Improved K-means Algorithm
Aiming at a variety of small picking problems of parts,in the multi-person collaborative picking mode,the task allocation is unrea-sonable,the picking time varies greatly,and the picking link is easy to timeout.A multi-person collaborative picking model aiming at the shortest picking time is constructed,and the improved K-means algorithm and genetic algorithm are used to solve the model.Aiming at the shortcomings of the traditional K-means algorithm clustering results,the number of picking points contained in each cluster varies greatly.The picking time of each cluster is used as an index to transform the cluster where the picking points belong.The genetic algorithm is used to per-form path planning and picking time calculation on the clustering results to obtain the optimal clustering results.Taking the parts picking pro-cess of a security equipment manufacturing enterprise as the research object,the effectiveness of the algorithm is verified by comparing with the picking time obtained by simple batching.
万方数据
维普
