In disaster relief operations, multiple UAVs can be used to search for trapped people. In recent years, many researchers have proposed machine le arning-based algorithms, sampling-based algorithms, and heuristic algorithms to solve the problem of multi-UAV path planning. The Dung Beetle Optimization (DBO) algorithm has been widely applied due to its diverse search patterns in the above algorithms. However, the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic, potentially leading to an inability to fully explore the search space and a tendency to converge to local optima, thereby not guaranteeing the discovery of the optimal path. To address these issues, we propose an improved DBO algorithm guided by the Landmark Operator (LODBO). Specifically, we first use tent mapping to update the population strategy, which enables the algorithm to generate initial solutions with enhanced diversity within the search space. Second, we expand the search range of the rolling ball dung beetle by using the landmark factor. Finally, by using the adaptive factor that changes with the number of iterations., we improve the global search ability of the stealing dung beetle, making it more likely to escape from local optima. To verify the effectiveness of the proposed method, extensive simulation experiments are conducted, and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm (GA), the Gray Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA) and the original DBO algorithm in the disaster search and rescue task set.

Mg-2Zn-1Al alloy was used as the matrix, and 0.2wt% Ca, 0.2wt% Gd, and 0.2wt% Ca+0.2wt% Gd were added into it. The target alloys with four components were extruded at 200℃ and extruded bars with good surface quality were obtained. Optical microscope (OM), scanning electron microscope (SEM), X-ray (XRD) and tensile mechanics experiment were adopted to analyze the effect of trace Ca and Gd on the microstructure and mechanical properties of Mg-2Zn-1Al alloy. It is found that the grain size of the as-cast matrix alloy can be refined by adding Ca and Gd, and the effect of grain refinement was the superposition of the two effects added separately. This is due to the heterogeneous nucleation of Al₂Ca and the segregation of Gd in front of the solid-liquid interface leads to the inhibition of grain growth. Furthermore, the addition of Ca and Gd can make the extruded micro-structure fine and uniform, which can weak the texture to improve the mechanical properties of the alloy. And the composite addition has the best refinement effect and texture weakening effect. Therefore, the alloy with the composite addition of the two showed the best mechanical properties.

To deeply understand the dynamic recrystallization behavior of as-cast AZ12 magnesium alloy in deformation process, the uniaxial hot compression experiments were implemented through systematic isothermal compression experiments. The true strain of thermal compression experiments was set to 50% with temperatures of 200, 250, 300, 350, 400 ℃ and the strain rates of 0.001, 0.01, 0.1, 1 s⁻¹. The Dynamic Recrystallization (DRX) kinetic model of AZ12 magnesium alloy was established and the accuracy of this model was verified. The model is used to predict the volume fraction of the sheet obtained by rolling through different rolling passes under the condition of consistent total reduction (50%). And the predicted results are in good agreement with the experimental results.