# A Survey of the Literature on Order-Picking Systems by Combining Planning Problems
## 5 Discussion
### Performance Measure
#### 5.2.3 Productivity  
Thirteen further studies focusing on the goal of maximization of productivity were reviewed. The reviewed articles pointed out that:  
1. Small size orders are performed with a great variety of parts.
2. Some orders will affect the efficiency of the order-picking process due to either the seasonality of the order, the intention of moving the order forward, or various delivery locations based on point-of-sale information. Table 7 shows an overview of the studied articles regarding the maximum productivity of the order-picking process.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Auditors** & **Assignment** & **Routing** & **Batching** & **Sequencing** & **Tardiness** & **Others** \\ \hline [PERSON] \& [PERSON] [56], [PERSON] et al. [61], [PERSON] & & & & & \\ et al. [50], [PERSON] \& [PERSON] [16], [PERSON] \& [PERSON] & \& & & \\ [51], [PERSON] et al. [42], [PERSON] \& [PERSON] [15] & & & & & \\ [PERSON] \& [PERSON] [55] & & & \& \& & \\ [PERSON] \& [PERSON] [59], [PERSON] \& [PERSON] [60] & & \& \& \& \& \\ [PERSON] et al. [18] & \& & & & & \\ [PERSON] et al. [62], [PERSON] et al. [67] & \& & \& & & \\ [PERSON] et al. [21] & \& & & \& & \& \\ [PERSON] et al. [13] & & \& & \& & & \\ [PERSON] et al. [30], [PERSON] \& [PERSON] [64], [PERSON] \& & & \& & & \\ [PERSON] [41] & & & & & & \\ [PERSON] et al. [36] & & & & & & \& \\ [PERSON] et al. [57], [PERSON] [58], [PERSON] et al. [63], [PERSON] & & & & & & \\ et al. [6], [PERSON] et al. [65], [PERSON] et al. [66], & & & & & & \\ [PERSON] \& [PERSON] [68], [PERSON] et al. [69] & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Overview of the reviewed articles in minimizing cost.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Auditors** & **Assignment** & **Routing** & **Batching** & **Sequencing** & **Tardiness** & **Others** \\ \hline [PERSON] et al. [48], [PERSON] et al. [70] & & \& & & \\ [PERSON] et al. [22] & & \& & & \& \\ [PERSON] et al. [67] & & \& & & & \\ [PERSON] et al. [90], [PERSON] \& [PERSON]. [80] & & & & \\ [PERSON] [95] & & & & & \& \\ [PERSON] \& [PERSON] [33], [PERSON] \& [PERSON] [85] & & & & \\ [PERSON] [58], [PERSON] et al. [72], [PERSON] et al. [32], & & & & & \\ [PERSON] et al. [69] & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 7: Overview of the reviewed articles in maximization of Productivity.  
As can be seen in Table 7, most studies have focused on routing and batching. However, [PERSON] et al. [67] simultaneously studied categories of assignment, routing, and batching to maximize the productivity in OPS. [PERSON] et al. [22] also simultaneously evaluated the effect of routing, batching, and sequencing on efficiency. [PERSON] et al. [67] tried to reduce the total processing time by focusing on the skill level of the operator and the individual difference between the pickers. They changed the batching methods and saved a total of 6% in time. They further used multi-level modeling and used the Adaptive Large Neighborhood Search algorithm to solve the model. In the warehouse, [PERSON] et al. [22] used a routing problem with a limited domain, which is not applicable to large-scale problems. They employed an integer model focusing on sequencing, batching, and routing, and used genetic algorithms to solve the problem. The above research works are more important than other ones in Table 7, but in the reviewed body of research, the role of operator skills was less seen.