Optimizing delivery scheduling with multiple storage locations

Abstract

In this report, supply chains of factory outlet stores are analyzed. Here, the concept of factory outlet stores have been investigated in literature to be able to understand which goal these stores serves. Based on a pull based supply chain perspective, replenishment has been investigated. Here, demand forecast, inventory, order ful_llment and transport have been considered. Here, transport models from literature are introduced to see which factors are considered and for which purpose these models can be used. Also, the performance of supply chain has been discussed, which consists of _nancial as non _nancial aspects. A case study will be done at the factory outlet store of L'Oreal. Here, the supply chain has been analyzed, as the catalogue and type of products they o_er. The replenishment policy has been analyzed, in which the transport process from the CPD warehouse to the store will be investigated. Here, a model will be designed to be able to schedule the deliveries to the store in a more cost e_cient way. An analytical modelling method is selected to develop a model which captures the mentioned transport process. Here, aspects of models in literature are evaluated to be used in the transport model for scheduling deliveries. The model is developed as an integer mixed linear programming model and will schedule the amount of pallets per delivery to a storage location, in which two storage location are presented. This model is described as the delivery scheduling transport model (DSTM) and is checked on implementation in MATLAB in a veri_cation step. The DSTM has been con_gured for the case study at L'Oreal, which is checked by a validation step to see if the model meets the system requirements. Then, experiments with di_erent inputs are executed to see if savings can be realized by scheduling the transport via this model. This is realized in all the inputs scenarios. To see if more savings can be realized, sensitivity analysis have been performed to investigate how parameters can be tuned to realize lower cost. A conclusion will _nalize this research to conclude that replenishment orders can be scheduled in a more cost e_cient way by the DSTM, which is the result of a case study of L'Oreal.