# Optimizing Aircraft Routes in Dynamic Conditions Utilizing Multi-Criteria Parameters
## 1 Introduction  
In today's aviation infrastructure environment, where the number of flights is constantly growing [1], flight path optimization is becoming an increasingly complex and urgent task [2]. Improving the efficiency of flight planning requires airlines and air traffic control authorities to consider a number of critical factors, such as efficiency, safety, effectiveness, and adaptation to changing weather conditions [3]. In this regard, existing algorithms for building optimal flight routes, such as A*, B*, D*, and Dijkstra, need to be constantly improved to ensure high performance and accuracy in the face of such external factors. The relevance of the outlined thematic focus is confirmed by the constant growth of air transportation and increased requirements for the speed and accuracy of flight planning. For example, according to the analysis of air transportation in Ukraine and the world [1], the global air transportation market is growing by several percent annually, which poses new challenges for aviation companies in terms of efficiency and safety [4]. In this context,improving existing algorithms and developing new technological solutions to optimize aircraft routes is an urgent task to ensure economic efficiency and safe aviation operations. Therefore, the study of flight path optimization algorithms, specifically their improvement and adaptation to specific conditions, is an important step towards improving the efficiency of flight planning and ensuring compliance with modern requirements in the aviation industry. **The object of research is aircraft route planning. **  
The subjects of research are the algorithms and methods for constructing optimal aircraft flight paths that need to be improved and adapted to dynamic environmental conditions, the application of which will increase the efficiency of air transportation. The purpose of this paper is to analyze current solutions and highlight the key features in the formation of a technology for determining the optimal flight path of an aircraft based on multi-criteria analysis. In this article, all analysis and research will be focused on the flights in upper airspace (Over 18,000 ft, Class A). This will improve flight planning, reduce the cost of operations, increase forecasting accuracy, and improve the system's ability to adapt to real, often unpredictable conditions during flights. To achieve this purpose, the following main research objectives were identified:  
1. Analyze the existing algorithms for constructing aircraft flight paths, such as the A*, B*, D*, and Dijkstra algorithms, and their improvements, which will allow planning the shortest route, taking into account additional safety and economic criteria. 2. Identify key features and requirements for information technology to optimize flight paths (including economic, safety, and operational criteria). This allows pilots, dispatchers (and other structural units of air transportation management) to choose the best routes and resolve critical situations (which may arise during the flight in the event of changes in various factors, such as weather conditions or dangerous situations with other vessels). 3. To evaluate the effectiveness of modern methods and algorithms for optimizing flight paths, taking into account dynamic changes in conditions and specific requirements of air transportation, which will improve speed and safety in dealing with critical situations in the event of an increase in flight duration. 4. To outline the general task of building optimal aircraft routes for efficient and safe routes in terms of many criteria, such as economic factors, weather conditions, aircraft characteristics, etc. This will make it possible to ensure maximum efficiency in the use of resources (fuel, time, and the technical capabilities of aircraft), minimize operating costs, and reduce the risks associated with dangerous weather events, air traffic disruptions, and technical limitations of the aircraft. 5.