We address challenges of unpredicted demand and propose a multiobjective optimization model to integrate a lot sizing problem with safety strategy placement and optimize conflicting objectives simultaneously. The novel model is devoted to a single-item multi-period problem in periodic review policy. As a safety strategy, we use the traditional safety stock concept and a novel concept of safety order time, which uses a time period to determine the additional stock to handle demand uncertainty. The proposed model has four objective functions: purchasing and ordering cost, holding cost, cycle service level and inventory turnover. We bridge the gap between theory and a real industrial problem and solve the formulated problem by using an interactive trade-off-free multiobjective optimization method called E-NAUTILUS. It is well suited for computationally expensive problems. We also propose a novel user interface for the method. As a proof of concept for the model and the method, we use real data from a manufacturing company with the manager as the decision maker. We consider two types of items and demonstrate how a decision maker can find a most preferred solution with the best balance among the conflicting objectives and gain valuable insight.

peerReviewed