## 2 Literature Review  
In this section, we summarize the main research studies for picker routing and storage location problems in warehouses with manual systems. It is important to point out that in the literature and in practice, there are two main levels of mechanization for collection in the warehouses, according to [5; 9]:  
1. Manual systems: They employ humans and are divided into three systems: * Picker-to-parts systems: high-level picking systems with man-aboard and low-level picking systems (manual pick). * The put system. * Parts-to-picker systems (AS/RS minloads, carousels, etc.). 2. Mechanized/automated systems: They use machines and are mainly used for valuable, small and delicate items, and are divided into two systems: * Automated picking. * Robot picking. This work concentrates on describing manual systems; in agreement with [5; 10], in the majority of warehouses worldwide, humans are employed for order picking, wherein the low-level, picker-to-parts systems are the most common; this is the system used by the company in the case study. On the other hand, according to [11; 12], the variety of elements and processes, and the high investments required to get automated or mechanized systems, are difficult to trust and invest in. Furthermore, despite advances in technology, people react more flexibly to shifts occurring in the order picking process. The reader is advised to [13; 14] for an overview of mechanized-automated warehouses systems. In relation to [15], in the literature, three main warehouse layouts are discussed:  
* Conventional warehouses or block design: aisles are parallel to one another (picking aisle), where the products to be retrieved are located (pick location). * Non-conventional warehouses: they have a flying-V shape, U-shape, fishbone or other non-conventional layout. * Models of general warehouses: structures are undefined, and instead, they use general distance matrices. As a result, most research on improvements of order-picking efficiency have considered conventional layouts as a solution for their storage location layout, which makes the study results easily transferable to other stores. Some woks, such as [16; 17; 18], present the shape of the warehouse with a single block, while [19; 20; 21; 22], have contemplated multiple blocks. In the same way, the aisle can be wide ([23; 24]), where the picking aisles are assumed to be wide enough to allow order pickers to go from one aisle to another, avoiding wait times as a result of aisle congestion. Nevertheless, studies such as [25; 26] contemplated general and non-conventional warehouses respectively. In manual picking, four activities represent the total time [2]: setup, searching, picking and travel times. The travel and picking times are the time needed to go to and between the picking aisles; the latter comprises the greatest part of the expense of retrieved shown in Figure 1, which is itself the most expensive part of warehouse operating expenses; thus, it is the main option to improve the performance of this process [6]. It also represents the only variable part, while the rest of the components (searching, setup and picking) can be considered constants [3]. As reported by [27] the travel time is determined by the total length of the tour realized for the picker. Based on the above, in the literature [19; 26; 27; 28; 29], the picker routing problem can be interpreted as a special case of the traveling salesman problem (TSP). According to [10], most of the order picking planning problems, such as the order batching or the picker routing problem, the latter being a generalization of the TSP, have been shown to belong to the class of NP-hard problems; thus, the combination of several planning problems also generates an NP-hard problem.