Research on location allocation optimization based on partial order classification
Aiming at the dilemma that it is difficult to accurately assign weights in the calculation of cargo relevance indexes in the cargo allocation model,a method that can be used to calculate the relevance by the order of weights is proposed by combining with the theory of partial order set.Taking Company Z's finished wine warehouse as the research object e,the Apriori algorithm is used to calculate the correlation between goods,and on the basis of which the partial order analysis method is used to classify the goods.Considering the frequency of finished wines,correlation and shelf stability,a space allocation optimization model is established,and the model is solved by genetic algorithm to obtain the final space allocation scheme.The study shows that the optimized scheme improves the picking efficiency,which proves the effectiveness of the model and algorithm.The conclusions of the study provide reference for reducing the cost of enterprise warehousing and improving the picking and distribution efficiency of the warehousing system.
location allocationpartial order analysiswarehousing systemApriori algorithmgenetic algorithm