## 5 Conclusions  
This research tackled a very important issue--stock management--using a methodology that complemented the decision-making process of stakeholders, rather than substituting it, with greater focus on the energy consumption of the solutions, in line with current environmental awareness. The study revealed a diverse array of promising solutions, effectively balancing energy consumption, holding costs, and shortage risk. This many-objective optimization approach highlighted an inherent trade-off: minimizing one objective inevitably led to increases in others. This places the decision-maker in a pivotal role, tasked with selecting the solution that best aligns with the company's broader strategic goals. These findings also echo the concept of Pareto optimality, a state where it is impossible to improve one objective without compromising another. In a business context, this often translates into making strategic choices regarding resource allocation--for instance, optimizing energy consumption might necessitate higher holding costs. While this study's unique modelling and objectives preclude a direct comparison with the existing literature, it underscores the importance of Pareto efficient solutions in navigating complex, multi-faceted challenges like energy management and inventory control. The absence of a one-size-fits-all answer reinforces the need for bespoke strategies that reflect individual company priorities and risk tolerance. The inclusion of energy consumption in the decision-making process can at first glance worsen the results--more energy efficient solutions tend to have a larger risk of shortage. However, brining awareness into this dimension can be useful in several ways. First of all, in scenarios were an improvement in energy consumption is achieved at a small cost to the other objectives, it provides a justification for decision-makers to select the said solution. Secondly, while choosing low-energy-consumption strategies may lead to larger risk of shortage, and consequently larger costs to the company, a focus on sustainability can provide marketing opportunities, as some industries benefit greatly from a stronger adherence to sustainability principles. According to [PERSON] and [PERSON] [50], sustainability initiatives \"_help companies establish a strong relationship with consumers, [...] which in turn creates a higher level of purchase intent and reduced sensitivity to price premiums_\". Figure 7: Parallel plot of the separated risk optimization for the complete solution space, only considering solutions with a risk of type 1 smaller than 400 and a holding cost larger than 4.8. Logistics systems are pivotal components in companies and are often overlooked when it comes to the application of optimization and artificial intelligence algorithms, often applied solely to the shop-floor operations. However, the application of energy-efficient and environmentally friendly planning strategies in logistics systems, such as the present optimization of the ideal stock at storage locations, can improve visibility into the objectives considered and provide better results than fixed stock strategies, while being cost-effective analyses. Additionally, manufacturing execution systems (MES) often overlook the dimension of energy management; the proposed approach tackles both issues: a central issue of MES--stock optimization--with energy consumption considerations. While this study demonstrates the effectiveness of many-objective optimization in balancing competing objectives in warehouse stock management, the model's focus on a single warehouse with specific storage types limits its generalizability to more complex supply chain configurations.