To address the challenges in coverage， forwarding and aggregation coordination of heterogeneous UAV clusters under damaged post-disaster infrastructure， a dynamic routing planning model is established with speed， heading angle and transmit power as control variables， which unifies UAV mobility， ground node coverage， link rate， buffer queue， functional backhaul capability and energy consumption within the same time domain. To tackle the deficiencies of the original L-SHADE algorithm， namely the lack of spatial information of task nodes in random initialization and the absence of coverage state feedback in parameter adaptation， a coverage-state-aware L-SHADE is proposed. The coverage-prioritized individuals are adopted to optimize the initial population. According to elite coverage violations， the proportion of feasible individuals and the trend of coverage variation， the algorithm switches among coverage construction， coverage stabilization， performance refinement and coverage recovery states， and constrains the p value， differential scaling factor F and crossover probability CR. Five independent runs are carried out in a fixed heterogeneous environment， and comparisons are made with the original L-SHADE and the L-SHADE only with coverage-prioritized initialization. Descriptive results from the five independent runs show that the average coverage rate of the proposed algorithm rises from 0.827 4 to 0.894 3， an increase of 6.69 percentage points or a relative increment of approximately 8.09%； the average coverage violation is reduced by about 37.64%， the average throughput increases by roughly 64.25%， the average queue load decreases by approximately 19.64%， and the average normalized energy consumption drops by about 6.0%， from 0.000 416 to 0.000 391. The above differences reflect the trend of numerical improvement under the current fixed scenario and small-sample conditions， and a statistically significant superiority cannot be concluded from these results. Within this evidence boundary， the results demonstrate that explicitly introducing coverage state feedback into differential evolution search facilitates a more coordinated search direction among coverage maintenance， data backhaul and resource consumption， and can provide methodological references for continuous communication service planning of heterogeneous unmanned platforms in low-altitude economy and post-disaster emergency scenarios.