## 1 Introduction  
Transport by road and air is one of the largest contributors to the highest greenhouse gas emissions and fuel consumption in the logistics industry. In recent years, due to rising carbon dioxide emissions and fuel costs, the issue of sustainable daily scheduling of transport operations aimed at reducing environmental pollution has attracted increasing interest and concern from large logistics companies. In such a situation, unmanned aerial vehicles (UAVs, drones) are not just a technological advancement based on modern ideas of artificial intelligence but actually provide a sustainable solution to green technologies in logistics, transport, and material handling. In this light, the ability of UAVs to carry out sustainable autonomous deliveries efficiently and effectively has been researched and explored by large logistics companies (e.g., DHL Express, UPS), e-commerce retailers, and companies (e.g., Walmart, Google) [1, 2]. The environmental benefits of UAVs are universal and intertwined with economic and social benefits; their environmental friendliness has systematically improved in recent years as drone delivery technologies (e.g., batteries, autonomous navigation, obstacle avoidance, and detection algorithms) have been greatly improved. Because drones are much smaller than trucks and airplanes, drones generally cost less and consume less energy and fuel per unit distance traveled. Furthermore, most delivery drones consume electricity, which can be generated from clean energy sources such as solar or wind, so they emit fewer harmful emissions per unit of energy consumed compared to traditional trucks and airplanes while also increasing the efficiency of clean technologies. We observe that the environmental benefits of UAVs are mainly driven by the overall benefits and profits of modern digital and artificial intelligence-based technologies. They were comprehensively studied and classified by [PERSON] and [PERSON] [3, 4]. Here, we select and highlight three main factors that directly lead to environmental benefits and economic profits:  
* Using battery-powered UAVs in the air instead of trucks on the road can significantly reduce energy and fuel expenses;
* It reduces environmental pollution, carbon dioxide emissions, and other negative impacts of transport processes on the environment;
* It improves the efficiency of clean technologies by increasing energy-saving efficiency. A broader and more detailed categorization of the relevant environmental benefits of UAVs is beyond the scope of this article. The interested reader is referred to the available comprehensive surveys and studies in this area cited therein [1; 2; 5; 6; 7]. It is known that scheduling and routing of vehicles subject to external, in particular, environmental constraints, is a complex combinatorial problem that, generally, is NP-hard, meaning it cannot be solved optimally for large instance sizes in reasonable (polynomial) computational time [8; 9]. In this regard, a practical alternative would be either to obtain efficient exact algorithms for practically important special cases of the problem or to develop fast and sufficiently effective approximation algorithms. Increased theoretical and practical interest in this problem and its applications has been noted, for example, in a number of reviews [1; 2; 5; 6; 7]. For a detailed description of various problem formulations, models, and corresponding algorithms for the general drone fleet assignment problem, we refer the interested reader to the surveys [10; 11; 12; 13; 14; 15], which provide excellent reviews of work in this area. In what follows, we limit our attention to graph models for maximizing the average UAV fleet profit and solve this optimization problem in strongly polynomial time, reducing it to a special type of parametric assignment problem.