The purpose of this article is to check and identify management gaps that lead to the formation of digitalization problems in enterprises in the context of Industry 4.0 and to offer a conceptual approach to managing the development of high-tech enterprises in digital transformation. The paper substantiates the concept of digital transformation management in a high-tech enterprise based on interdependent adaptive systems for planning digital transformation processes, monitoring, and change management. The paper considers the idea of the Industry 4.0 concept and presents principal technologies and tools that contribute to the gradual transition to digital transformation. It is determined that digital transformation is a process of transition to digital business, which involves the use of digital technologies to change business processes in the company and provision of new opportunities for additional income and development prospects. A conceptual model of enterprise competitiveness formation in the process of digital transformation has been developed, which includes organizational and economical digital tools for sustainable development of high-tech enterprises and synergies from the organization of new forms of digital interaction. The proposed methodology for managing the development of high-tech enterprises in the context of digital transformation is based on the formation of an ecosystem model of decentralization in a single distributed digital space, based on interconnected adaptive systems of planning, monitoring, and change management, and, on the basis of modeling and forecasting of complex manufacturing and logistics processes of high-tech industries, it allows effective implementation of the innovative order portfolio in the short term and with limited opportunities while coordinating the priorities of the business strategy and strategy of digital transformation of high-tech enterprises.

This article describes and investigates the planning aspect of military actions aimed at destroying enemy targets with the help of an attack drone swarm. This study attempts to solve the task of operational-tactical planning of a massive attack on enemy targets with the help of combat drones, which have different combat potential characteristics. It analyzes the problems of unmanned aerial vehicles (UAVs) swarms’ usage, which ensures maximum efficiency during combat operations. The article shows that in order to plan effective military operations, it is necessary to form the following logistical sequence: identification of relevant targets set, formation of drones into a swarm to attack targets, distribution of drones by targets, and planning flight routes of a drone swarm in conditions of military threats. It concludes that for the effective use of a combat drone swarm, it is necessary to plan logistical actions in advance to inflict maximum damage on the enemy and successfully fulfill the operational and tactical goals of the military leadership. The purpose of this study is to create information technology models that will allow planning logistical military actions for the effective use of combat drone swarms to defeat enemy targets. This article describes a systematic representation of logistical military operations for combat drone swarms. It also analyzes enemy targets, which are represented in the form of a priority list with the characteristics of relevance, the necessary combat potential to hit the targets, the risks of approaching the targets, and the flight time of the drones. From the list of targets, a sublist is formed, considering the combat potential of the drone swarm and the necessary potential to defeat the selected enemy targets. The optimization model helps to distribute the swarm of drones into groups to achieve the enemy targets and destroy them. The movement of drones is planned considering flight zones, possible anti-drone actions of the enemy, and the risks of military threats. Any Logic agent simulation platform can be used to create a simulated flight model of a drone swarm to selected enemy targets. Modeling makes it possible to form rational flight routes of a drone swarm under conditions of military threats from the enemy. An example is given to illustrate the formation of logistical actions for planning a massive attack on enemy targets with the help of a drone swarm. The scientific novelty of this study is related to the solution of the urgent problem of planning logistical military operations for the effective use of a combat drone swarm to destroy enemy targets. The results of this study should be used for the operational and tactical planning of logistical military operations to defeat enemy targets with the help of a combat drone swarm.

The development of enterprises in strategic industries depends on funding made innovative products that are in demand in the markets for high-tech products. The interest of investors depends on the innovation and competitiveness of the products that the enterprise can produce. The enterprise should make a new, diversified portfolio of orders to attract funding from potential investors. The innovativeness of the product is determined by the novelty of the components in its composition. Therefore, the pressing challenge is to study the innovation of high-tech products based on their component architecture. It makes it possible for investors to assess the possibility of enterprise financing while making a promising diversified portfolio of orders. The study develops a method to justify investments into the new orders that are based on the research of the component architecture of the complex product. The tasks analyzed the product component architecture innovation and investment attractiveness, justify and select the diversified portfolio of orders, simulate and assess orders portfolio feasibility are stated and solved. The paper proposes the component method that makes it possible to evaluate the architecture of the new product in terms of innovation and investment attractiveness. The research of innovation is conducted depending on the composition of the components in the architecture of the whole product. These components can be either new that require a new cycle of creation, or “old” ones, taken from previous experience with the possible adaptation to the technical requirements of the new product. By using the proposed multifactor planning of the experiment, the possible options are considered and the main indicators of the new product are assessed: investment attractiveness, costs, timelines, and risks of order fulfillment. Using lexicographic ordering of alternatives the compromised selection of the optimal option in terms of limited capabilities of the enterprise is conducted. To optimize the diversified portfolio of orders the method of integer (Boolean) programming is used. Investment attractiveness is used as a target function. The restrictions consider allowable costs, timelines, and risks of the orders portfolio fulfillment. In the last part of the paper, the method of simulation agent modeling in a form of applied information technology is used to assess the timeline for order fulfillment and the impact of risks on the feasibility of the diversified portfolio of orders. The novelty of the results is related to the justification of the choice of a diversified portfolio of orders, which in contrast to the already existing approaches, is based on the advanced component architecture of complex products and the simulation of orders portfolio selection considering innovation and investor interests. The proposed method and information technology are planned for the future development of an enterprise that makes it possible to assess the competitiveness of products, as well as the possibility to attract funding.

This article solves the relevant task of studying military operations on a massive wave attack by a swarm of strike drones against enemy targets in a combat zone (CZ) of a military conflict. This research solves operational and tactical tasks for planning active actions on the battlefield by applying a massive strike on enemy targets by a swarm of combat drones (kamikaze drones). Therefore, the topic of the proposed publication is relevant; it analyzes and explores the sequence of logistical military actions to plan a massive attack using waves of strike drones. The purpose of this study is to create a set of models for applied information technology that will allow planning logistical actions for the effective use of a strike drone swarm to conduct a massive wave attack on enemy targets. This article analyzes problems associated with the formation of a swarm of drones, splitting the swarm into groups, and forming waves for active combat operations on the battlefield. Enemy targets will be attacked by strike drones in the waves formation, which makes it possible to carry out further successful operational and tactical actions. This study assesses the combat capability of a swarm of drones required to defeat enemy targets in a military conflict zone. It creates a systematic representation of the sequence of actions taken to plan a massive drone swarm attack, considering the combat capability and number of drones. With the help of military experts, the composition of the actual CZs is formed, in which the targets must be hit in the first place. The swarm of drones is rationally divided into groups that are directed to a set of targets in the CZs, considering the combat capability of drones to defeat targets. Waves of strike drones are planned to maximize damage to enemy targets. This research analyzes possible directions of drone movement toward enemy targets despite military threats. The models form flight routes of drones swarming to enemy targets under the conditions of possible anti-drone actions. An agent model was created using the Any Logic platform to simulate drone flight and form the routes of the drone swarm groups. This article presents an illustrated example of planning logistical actions to use waves of strike drone swarms for a massive attack on enemy targets. The scientific novelty of this study is related to solving the relevant problem of preparing and planning logistical actions for a massive attack on enemy targets using waves of strike drones by creating a set of optimization and simulation models that contribute to the effectiveness of further military attack operations on the battlefield. The results of the study could be used by military leaders to plan the use of a drone swarm to launch a massive attack on enemy targets in a military conflict zone.