Multiobjective Optimization of Complete Coverage and Path Planning for Emergency Response by UAVs in Disaster Areas

Complete Coverage and Path Planning methods operate on many models depending on initial constraints and user demands. In this case, we optimize paths for a set of UAVs in the disaster area divided into rectangular regions of different sizes and priorities representing the expected number of victims. Paths maximize the number of victims localized in the first minutes of the UAVs’ operation and minimize the entire operation makespan. The problem belongs to the domain of multiobjective optimization; therefore, we apply the Strength Pareto Evolutionary Algorithm 2, which is equipped with several problem-specific perturbation operators. In the experimental part, we use SPEA2 to four selected test cases from a TCG-CCPP generator powered by actual data on residents in selected regions in Poland published by Statistics Poland.