Track: Inventory Management
Every industry is competing, especially retail, to transition or increase its sales channels not only through physical stores, but also through online channels. Likewise, warehouses are required to be able to participate in the order fulfillment process both through stores and online. This research develops an inventory model for dual channel warehouses with limited warehouse space and product returns. With the warehouse divided into two parts, namely for offline order fulfillment and for online order fulfillment. The development of this model also considers demand uncertainty and delivery lead time. The warehouse space constraint is convex nonlinear programming and uses Karush-Kuhn-Tucker analysis in solving it. A closed-form solution was developed using normal distribution in the case of no limited warehouse space constraints, and an iterative algorithm using bisection method for the case with limited warehouse space constraints. Numerical analysis was conducted directly on a warehouse in a sports retail company to get a real-world view of the proposed model. The results show that warehouse space greatly affects the size of the order quantity. The sensitivity analysis conducted also shows that the proposed model offers an optimal solution for the size of the order quantity and reorder point and can also minimize the total warehouse cost.