# Non-Traditional Layout Design for Robotic Mobile Fulfillment System with Multiple Workstations
## 1 Introduction  
Driven by the global trade expansion and the world economy reformation, the logistics sector has grown rapidly over the past few decades [1], triggering a tremendous increase in freight transportation (e.g., road transportation, [2]; maritime transportation, [3]; air freight transportation, [4]), and enabling growth in cargo volumes handled at different types of terminals (i.e., warehouses, [5]; rail terminals, [2]; cross-docking facility, [6]; marine terminals, [4], etc.). Unfortunately, this also causes negative impacts on the environment to some extent (e.g., carbon emission [7]), and thus, enhancing the efficiency of freight transportation and creating a more sustainable logistics system is of great importance for both enterprises and the society. Among the aforementioned terminals, warehouses are perhaps the ones most relevant to the e-commerce community. Typically, warehouses are labor-intensive that include receiving, storage, order-picking and shipping processes. Among these, the order-picking process has been identified as the most labor-intensive and costly activity for the operation of warehouses ([PERSON] et al. 2007, [8]). To curb operational costs and increase throughput capacity of warehouses, more and more companies adopt new storage and order-picking technologies, especially e-commerce businesses with fast turnover of goods and strong demand fluctuations. For instance, Kiva System,also called Amazon Robotics, saves pickers a lot of running back and forth fetching items from the shelves ([PERSON], 2012, [9]). The implementation of this kind of system can be seen in Amazon.COM, Alibaba.COM and JD.COM China. This type of warehouse system is referred to as a robotic mobile fulfillment system (RMFS) ([PERSON] et al., 2017, [10]), where robots hoist movable storage pods (i.e., inventory pods) and deliver them directly to the workstations for stationary pickers to retrieve required items. Unlike the traditional order-picking system, which requires pickers travel to each storage rack, this emerging parts-to-picker system allows the picker to concentrate on picking and packing orders ([PERSON] et al. 2017, [11]). There remain numerous factors impacting the order-picking process in a warehouse, including warehouse layout, storage strategy, zoning, batching and routing method (see [PERSON] et al. 2007 [8] and [PERSON] 2009 [12]). The warehouse layout is one of the most important components [13], which will affect the daily operations ([PERSON], [PERSON] and [PERSON] T, 2012 [14]; [PERSON] et al. 2015 [15]). Typically, in a traditional warehouse, picking aisles must be straight and parallel to each other; cross aisles should meet picking aisles at right angles, which forces pickers to travel rectilinear distances to picking locations. However, [PERSON] and [PERSON] (2009) [16] break these rules and propose two novel aisle designs for the unit-load warehouse with a single pickup and deposit point (here referred as a workstation), i.e., so-called flying-V and fishbone, which can reduce expected travel distance by about 8\(\sim\)12% and more than 20%, respectively. [PERSON] and [PERSON] may be the first to study non-traditional warehouse design after [PERSON] (1972) [17] put forward the optimum warehouse design with radial aisles. They extended their study to facilitate multiple pickup and deposit points using a flying-V layout ([PERSON] et al. 2012 [18]), which can save 3\(\sim\)6% of the travel distance compared with a traditional layout. Inspired by these research efforts, we think it would be very interesting to investigate the performance of new layout designs under the context of a robotic mobile fulfillment system. It is worth mentioning that another similar scenario to the aforementioned issue is container picking in port yard systems and their layout design (see [19; 20] for more details). Typically, in such systems, containers are carried by ground trolleys, shipped to quay cranes, and finally loaded to vessels.