Combining Simulation and Optimization to Improve Picking Performance on a Specialized Retailer Warehouse

The importance of warehouses have on companies ’ supply chain has been increasing in the past few years. This pressures warehouses in attempting to decrease costs to become more efficient. In the supply chain a warehouse can serve many purposes such as taking advantage of forward buys, meet uncertainties in the supply chain and many more. While these tasks are beneficial for the supply chain, the very labor intensive operations inside the warehouse can mean significantly high operating costs. Therefore, any inefficiency can be seen as a major opportunity for cost reduction. Among the most vital decisions in warehouse planning is the storage assignment policy. The decision of where to locate the products inside the storage space of the warehouse has been proven to have a considerable impact in the overall warehouse productivity. To tackle this problem a methodology that can be used to select a best overall storage assign-ment policy was developed. The methodology combines simulation and optimization to design test and evaluate alternative policies. The first part of the methodology is used to characterize picking performance, next an optimization method is used measure the expected performance of each policy and afterwards the storage assignment policy is tested under uncertainty. The results achieve by this methodology look promising and show that it can be used to tackle the storage assignment policy on a more operational level, instead of the more frequent tactical level. In the case study tackled by this thesis, the estimated reduction of the expected order-picking travel time achieved was of 17%. i i