The intuitive approach of determining the positions of the ordered goods in the warehouse for each received order and calculating the shortest route from there is not advisable for various reasons. On the one hand, depending on the layout of the warehouse, as in the case of the so-called Traveling Salesman Problem (TSP), an NP-complete problem may arise whose optimal solution cannot be calculated efficiently. Even if a calculation of this solution is possible and an optimal route can be determined, this calculation can take a lot of computing time for larger warehouses. Therefore it makes sense to use heuristic approaches, which are more efficient in the calculation and also provide very good solutions.
In addition, significantly shorter overall routes can usually be achieved by combining several orders into one route. Since both routing and batching occur at the operational level, it is obvious and promising to solve both problems together. For the simultaneous calculation of batches and routes, some efficient combined heuristics exist (Cheng, Chen, Chen, & Jung-Woon Yoo, 2015) (Kulak, Sahin, & Taner, 2012) (Li, Huang, & Dai, 2016) (Lin, Kang, Hou, & Cheng, 2016).
As mentioned in the introduction, not only routing and batching, but also storage allocation and routing must be considered together. This is because much better solutions can be achieved if coordinated heuristics are used to decide where goods are stored and to determine the shortest possible routes. In the following section, we want to give an impression of which heuristics can be used here, how the different heuristics interact and what quality the calculated solutions have.