Jul 2026· GECCO Companion· pp. 1327-1334· 0 citations· 25 references
Computer Science
TL;DR
A new set of objective functions to maximize the number of detected victims in the earliest stages of the search while minimizing completion time is proposed and a new solution representation is introduced together with problem-specific mutation operators.
Abstract
The benefits of early reconnaissance in the event of emergency response can be invaluable for the success of the emergency teams present in the area. The use of unmanned aerial vehicles (UAVs), which are restricted only by weather conditions, introduces a path-planning optimization requirement. We model a disaster area as a set of rectangular regions, prioritized by the expected number of victims. UAVs, working as a team, provide complete coverage of all regions to gather information about conditions on the ground. This paper proposes a new set of objective functions to maximize the number of detected victims in the earliest stages of the search while minimizing completion time. A new solution representation is introduced together with problem-specific mutation operators. Experimental research using NSGA algorithms provides insight into how the model's features affect solution optimization.
Damaged transportation infrastructure and delayed, making timely emergency response difficult. To address this, we develop a multifunctional UAV location–routing optimization model with time-window and energy constraints, where UAVs perform both relief delivery and damage reconnaissance. We propose an LLM-based adaptiv...
Yan He, Pan He, Dongqing Zhang· International Conference on...· 0 citations
Abstract. In recent years, the increasing frequency of natural disasters in remote and rugged areas has underscored the importance of unmanned aerial vehicles (UAVs) for rapid emergency response. This paper presents a novel approach for optimizing the placement of UAV docking stations in mountainous terrain for emergen...
Yi-Lang Lin, Zhi-Yong Wang, Yong-Jie Lin et al.· The International Archives o...· 0 citations
Simulation experiments show that in a complex obstacle environment of 100m × 100m× 100m, the IAGA algorithm can effectively plan the optimal path, and the convergence speed is significantly improved compared to traditional genetic algorithms, verifying the effectiveness and robustness of this method in handling multi-c...
Qian Wan, Tian-En Lu, Liquan Huang et al.· International Conference on...· 0 citations
Efficient relief supply delivery within the golden 72 hours after a disaster is critical to reducing casualties. For medium-to-large unmanned aerial vehicles (UAVs), pre-flight preparation—including payload mounting, center-of-gravity confirmation, flight route distribution, and link/airspace checks—is abstracted as re...
Jiang-Wei Zhao, Qi Feng, Cheng Zhu et al.· 2026 12th International Conf...· 0 citations
An improved deep Q-network (DQN) algorithm is proposed, introducing a priority experience replay mechanism to improve sample utilization, and designing a composite reward function including arrival reward, step penalty, direction guidance, and safety penalty to guide the UAV to plan safe and efficient flight paths in c...
Rui Qin, Han-Jing Zhou· International Conference on...· 0 citations
The greedy heuristic of the BaF algorithm was combined with the computational power of a multi-threaded system and subtly designed search bound adjustment strategy and then a new approach called the Parallel Planner for short PPlanner was developed, ranked as the second or third best path planner for the remaining case...
S. Aslan, S. Çoban, Tuğrul Oktay et al.· Aeronautical Journal· 0 citations
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