# A Survey of the Literature on Order-Picking Systems by Combining Planning Problems
## 6 Results
The obtained results confirmed that all planning problems must be incorporated due to different time horizons of decisions made one after another. As different industry managers look for ideal, simple, intuitive, and reliable solutions, cost reduction solutions are suggested in the order-picking process. Table 3 indicates an insufficient balance between decision-making variables about planning problems as well as a tendency towards more studies about routing and storage space at a higher speed than other aspects. Additionally, taking the 27 articles on cost minimization, it is clear that this issue has not been sufficiently surveyed. It should be noted that cost reduction includes a wide range of issues, one of which is tardiness that can reduce costs. Although industrial automation has an increasing impact on the industry as well as the OPS system, the studies reviewed from 2014 onwards [6, 18, 21, 30, 36, 61, 41, 42, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 64, 66, 67, 68, 69] continued to focus directly on warehouse activities such as routing, batching, and assignment to reduce costs. This shows the importance of costs in the OPS process, so that in this study, 77% of cost-related studies were published from 2014 onwards. Concerning the literature and methodologies of research works carried out in the area of order-picking, it was found that most of the research works emphasized mathematical programming methods with a 64% allocation percentage (Figure 10). Moreover, the genetic algorithm, ant colony, variable neighborhood search (VNS), particle swarm optimization (PSO), and other heuristic methods were significantly employed (Table 10). Furthermore, based on Table 10, mathematical programming methods have been mainly used for routing and batching problems to explore the aspects of the picking process simultaneously. This suggests that the majority of researchers have tried to minimize distance in order to reduce cost and time, mainly because routing is metric and calculable. Moreover, at the operational level, there is still a need to integrate more planning problems and calculate the real-world features. Despite the importance of human resources in the warehouse environment, a small number of articles have evaluated the labor planning problems, such as determining the daily labor force level, assigning the labor in order-picking areas, and assigning jobs to pickers [6, 7, 65]. It should be further noted that as the warehouses offer multiple services to customers, the availability and performance of human resources ensure the quality of service to customers and the performance of order-picking. For instance, determining the level of the workforce combined with the assignment of order pickers and the planning problem makes focusing on the number of pickers a challenging opportunity for future research. Previous studies have mainly focused on reducing order-picking time. Working in an atmosphere with increasing pressure and limited time raises the likelihood of selection errors. In recent years, the number of articles analyzing multi-objective picking planning problems has risen dramatically. Nonetheless, currently, research works are mostly on the storage location, order batching, and routing. At a tactical level of picking problem, little attention has been paid to research. Previous studies have not only combined planning problems but have also simplified the order collection systems. The results developed in this paper indicate the need for more research on the congestion of warehouse aisles and the combination of picking operations problems in the future. In terms of cost reduction, the combination of tardiness with other planning problems has not yet been investigated. In addition, to improve efficiency, few studies have been performed in the field of assignment, sequencing,and tardiness, and the effect of different combinations of these problems on productivity improvement has not been studied. Moreover, the effect of combining planning problems has been only studied by [PERSON] et al.