Assignment of duplicate storage locations in distribution centres to minimise walking distance in order picking

With the rapid development of e-commerce, the orders processed in B2C warehouses are characterised by heterogeneous and small volume. The traditional storage assignment strategies used in the picker-to-parts warehouses do not have advantage any more. In this case, the scattered storage strategy is a good alternative. In this paper, we study a new scattered storage strategy that allows the same product to be placed in multiple storage locations. The correlation between products which reflects how frequently any two products will be ordered together in the same order is considered. The problem is formulated as a 0-1 integer programming model to minimise the weighted sum of distances between the products, with weight being the elements of the correlation matrix. To solve large-scale problems, a GA and a basic PSO algorithm are developed. To improve solution quality, a new PSO algorithm based on the problem characteristic is designed and a hybrid algorithm combing it with GA is proposed. Experiments show that the solutions of these algorithms are close to the optimal solutions for the small-sale problems. For larger problems, the specially designed new PSO greatly improves solution quality as compared to the basic algorithms and the hybrid algorithm makes further improvement.

Automated summary

With the rapid development of e-commerce, B2C warehouses are facing the challenge of processing heterogeneous and small volume orders. Traditional storage strategies are no longer advantageous, leading to the exploration of scattered storage strategies. A new scattered storage strategy considering product correlation, formulated as a 0-1 integer programming model, was proposed in this study. GA and basic PSO algorithms were developed for large-scale problem solving, with a specially designed new PSO algorithm and a hybrid algorithm showing improved solution quality.