# Optimizing Aircraft Routes in Dynamic Conditions Utilizing Multi-Criteria Parameters
## 6 Conclusions  
The paper analyzes modern solutions and identifies key features in the formation of a technology for determining the optimal flight path of an aircraft based on multi-criteria analysis. This makes it possible to improve flight planning, reduce operational costs, increase forecasting accuracy, and improve the system's ability to adapt to real, often unpredictable conditions during flights.  
It has been established that the improvement of the A*, B*, and D* algorithms and their variations increases the efficiency of aircraft flight route planning, in particular, by reducing the cost of resources and time. This was achieved through the use of optimizations based on Euclidean and Manhattan heuristics, which minimize computational costs at each stage of the search. As a result, the accuracy and speed of route construction have been improved, which helps to reduce overall costs and speed up request processing.  
The B*, B_Lite*, and enhanced B* algorithms were found to be particularly effective for working in large spaces. This is based on an analysis of their ability to quickly process large amounts of data. Thanks to optimization based on the use of data compression, these algorithms can work with greater accuracy and speed, which contributes to increased performance in large-scale routing tasks.  
It has been shown that the D_Lite* and D-focused* algorithms are characterized by rapid adaptation to changes. This is achieved due to their structure, which allows for updating calculations in real time. The effect of this is to increase efficiency in changing conditions, but the algorithms remain limited in versatility and computational costs.  
We analyze the Dijkstra algorithm, which can significantly reduce the search time. This was achieved by creating an effective iterative structure. This approach saves time in cases with stable conditions but requires specific initial conditions to achieve optimal results. For optimal performance, the Dijkstra algorithm requires the following specific conditions: negative edge weights, fixed start and end points, graph stationarity (unchanged weights and structure during computation), graph connectivity (existence of a path between all nodes), and a graph size limit to ensure efficiency in large-scale systems.  
An algorithm for building optimal flight routes for aircraft, taking into account variable conditions (in particular, weather conditions and fuel consumption), has been developed. This was made possible by integrating meteorological data and fuel consumption parameters into the algorithmic structure. The result is an increase in the accuracy of route forecasting and optimization of resource consumption.  
Practical studies [Table 10] have confirmed that the application of the developed algorithm can reduce flight time and fuel consumption for aircraft. This was achieved through detailed modeling of flight trajectories (for example, for the Airbus A320 neo, the flight duration was reduced to 7.0 h and fuel consumption to 2.45 L per hour). This reduction in costs has a positive impact on flight efficiency and reduces operating costs.  
It was found that the improved solution adapts better to changing weather conditions. This was established by testing in conditions of variable meteorological parameters. As a result, it saves resources and increases flight stability in adverse conditions, which improves the overall reliability of route decisions.  
Conceptualization, O.S. and N.L.; methodology, O.S. and L.S.; validation, O.S., L.S. and R.M.; formal analysis, O.S.; investigation, O.S.; resources, O.S., L.S. and Y.M.; data curation, R.M.; writing--original draft preparation, O.S.; writing--review and editing, O.S., N.L., R.M. and Y.M.; visualization, O.S.; supervision, N.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in this study are included in the article.  
The authors declare no conflicts of interest.