In the EC logistics business, which ships products upon receiving orders from customers via the Internet, determining the products to be handled and their inclusion ratios are a fundamental problem to be solved to increase the expected profit. It is difficult to find a good solution in a finite time because the number of products handled in EC is more than several million and the number of combinations increases explosively in the order of nth power. We formulated this problem as a portfolio optimization problem and tested whether it is possible to find an optimal or good solution using Markowitz's mean-variance model. The motivation for applying the mean-variance model, which is usually used for diversified investment in stocks, to EC logistics is that the model is very simple because it is obtained by the expected value and its variance, and it is easy to apply to the modeling of indicators such as sales and inventory cost in EC logistics. In logistics, it is easier to control inventory management and logistics costs if demand fluctuations are mitigated and leveled out as much as possible. The mean-variance model, which considers fluctuations as risks, is easy to apply to EC logistics because fluctuations tend to lead to higher costs. In this study, we constructed a mean-variance model of sales and inventory turnover using actual EC logistics data, and confirmed the effectiveness of the method for determining a preferred product portfolio from both EC and logistics perspectives.
