| dc.description.abstract | The impacts of global warming extend beyond the rise in temperatures, further affecting the Earth′s ecological environment and even causing irreversible effects such as species extinction. Therefore, effectively reducing greenhouse gas emissions has become a significant issue. To mitigate global warming, the use of renewable energy is indispensable. Currently, the main renewable energy sources include solar and wind power. These renewable energy sources are highly dependent on weather conditions, leading to instability in their energy supply. For the unstable energy supply, energy can be stored during off-peak periods and transferred to peak periods for use. This method allows energy to be delivered to demand points when needed, solving the problem of energy shortages and simultaneously increasing the utilization rate of renewable energy.
In summary, this study focuses on researching how to transport mobile batteries to demand points with the goal of maximizing the power demand that can be met. Considering real-world situations, time windows are added to each power demand point to restrict the delivery time, and limitations are also set on the capacity and delivery distance of the transport vehicles. Based on the above, a mesh path map is used to simulate the real-world setting of demand points. The problem itself belongs to the VRP (Vehicle Routing Problem) formed by paths, where the length of the paths is also a factor to consider. Therefore, an adaptive ant colony algorithm is used to solve the problem. The improved algorithm is based on the fundamental ant colony algorithm and is adjusted according to the characteristics of the problem. Through experiments on different types of problems, the feasibility and parameter combinations of the algorithm are adjusted, verifying that the improved algorithm provides better objective values in solving the problem of this study. | en_US |