Capacitated Generalized Traveling Salesman Problem Under Random Storage

Nowadays, e-commerce is more and more important in our daily life,and the number of companies who doing e-commerce is bigger and biggeras well. However, the competition for e-commerce companies is not onlyfrom the traditional retailers, but also from the other online retailer. How tostand out in the fierce competition becomes the topic which is highlyconcerned by the online retailers. Comparing with the traditional retailers,the most different characteristic of e-commerce is in their logistics storageand deliver part, which is also the key part for the online retailers tomining the extra profit.Today, most of the warehouse storage link, although according to thestorage unit of storage device partition management, but in order toimprove storage utilization, a tray piled area stored for many commodities,picking operation looking for a long time, reduce picking operatingefficiency: the same problem still exist in shelf area. Store and picking areainventory are not managed effectively, witch resulting in the interruption oforder picking, and picking process triggered emergency replenishmenttasks need to rely on skilled workers looking job complicated, inefficient.In selecting the link, not instant issued chosen to set the order pool,resulting in the tasks issued continuity poor, often there will be staff idle,not order typed processing, single pieces not issued a strict distinctionbetween task job links to increase the impact of operating efficiency. Andthe reservoir area, the pickers during a single task, any natural need tofinish the game picking, resulting in the empty go a long time, the pickingdensity and picking efficiency are relatively low.The background of this paper is Amazon’s warehouse-the random storage warehouse. The utilization of the warehouse can be improved byrandom storage strategy, thereby reducing storage costs. In such occasion,we do the research of the pre-treatment of the orders, and the optimizationof the picking route. We also give the model of the capacitated generalizedtraveling salesman problem, and model analysis, then solving it by thevarious neighborhood search algorithm, whose initial solution is given byCW-saving algorithm. Finally, proving the effectiveness of the algorithmby solving numerical examples.