Automated Application of Inventory Optimization
We present automated application of inventory optimization based on sales forecast. Inventory stock optimization is very required issue by companies recent years, however inventory models are based on the sales expectation. Therefore, the problem of optimizing inventory stock is divided into two parts, sales forecast and setting optimal inventory. We describe an automated solution to model selection for sales forecast and the inventory setting based on those predictions. In the end, we present our validation of the system through historical simulation. We compare simulations results against real inventory levels. Due to the large number of different length time series, this simulation was run in parallel on cluster and was parallelized in R. The algorithms were developed and tested on inventory time series from real data sets of the K2 atmitec company (Sales forecasting and inventory optimization are parts of ERP solution K2, which is provided by K2 atmitec s.r.o. company, http://www.k2.cz/en/).
KeywordsInventory optimization Sales forecasting Model selection Parallelization
This work was supported by The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II) project ‘IT4Innovations excellence in science – LQ1602’ and from the Large Infrastructures for Research, Experimental Development and Innovations project ‘IT4Innovations National Supercomputing Center – LM2015070’.
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