# Towards Productive and Ergonomic Order Picking: Multi-Objective Modeling Approach
## 6 Discussion
In contrast, in the health risk-based objective function, the increase was around 33% for both types of racks. Figure 10 visualizes results from different single- and multi-objective functions. Their use resulted in different assignment scenarios and different energy expenditures needed to prepare orders. Maximum energy consumption is the result of optimization with health risk-based objective function and multi-objective emphasizing health risk. As expected, energy consumption is higher in longer storage corridors and scenario 3 (S3) where heavy boxes predominate. Figure 11 visualizes results from different single- and multi-objective functions. Their use resulted in different assignment scenarios and different health risks values. Figure 10: Comparisons of energy expenditures from different objective functions. The health risk value is calculated so that it has a message value, which has not been found in the scientific literature so far. Attention should be paid to scenarios where the health risk value exceeds 30,000. This means that it demands one or more unacceptable postures with recommendations for immediate corrective measures. The health of order pickers is more endangered in short racks than in long ones, especially in the case of energy optimization. One of the more important findings is concluded from the results in Table 9. Regardless of which differently weighted multi-objective function is used, we consistently achieve a considerable reduction in health risks compared to the solely time-based single-objective function. The theoretical contribution of this study is in a developed solution to a storage assignment problem using a multi-objective model including time, energy expenditure and health risk based on binary integer linear programing with the possibility of a different weighting of individual optimization criteria. By counting the number of very risky postures for employee injuries, we determined a new view on the inclusion of health risk in treating warehouse assignment problem. We can give practice recommendations based on comparing several different optimization models or changing weights within the multi-objective model. The practical contributions of this study can be described with managerial insights:  
* Managerial insight #1. Less strenuous and safer work requires longer operating times and results in lower productivity. To overcome this issue, managers should use multi-objective optimization models to reduce health risk significantly at the cost of a small increase in time consumption, below 5% in short racks and below 10% in long racks. A single-objective health risk-based assignment is suitable from a managerial perspective for a time frame when the number of customer orders is low. It is also ideal for warehouses where rush hour traffic can be rescheduled throughout the working day. Figure 11: Comparisons of health risk values from different objective functions. * Managerial insight #2. Energy optimization is less tiring for employees, but solely energy optimization or multi-objective optimization emphasizing energy has not proven very suitable in practice. They both increase the number of very risky postures for employee injuries. A very-high health risk level stands for one or more unacceptable postures that need immediate corrective measures. Such cases should not occur in practice, as each occurrence poses a direct threat of immediate injury. * Managerial insight #3. Employee health is becoming increasingly important. When buying a warehouse management system (WMS), pay attention to the possibility of taking order picker's factors into account when optimizing work in the warehouse.