PROJECT MANAGEMENT: INDUSTRY SPECIFICS

The object of this monograph is the scope of implementation and individual project management processes in various fields of human activity.

In the first section, the problem of identifying configuration elements (CE) of an IT product has been solved. To solve the problem of identifying functional CEs, it is proposed to use hierarchical and non-hierarchical clustering methods. As examples of hierarchical clustering methods, the agglomerative clustering method AGNES using the nearest neighbor algorithm and the divisive clustering method DIANA have been proposed. As an example of non-hierarchical clustering methods, the k-means algorithm is proposed. For comparison with these methods, one of the graph-analytic clustering methods has been used, which has been developed to solve the problem of decomposition of the description of the monolithic architecture of a software product into separate microservices. A comparative analysis of the solution progress and the obtained results of solving the problem of identifying functional CEs using all four selected clustering methods has been carried out. It has been established that the best alternative is to use hierarchical clustering methods to solve this problem.

In the second section, methodological foundations and scientific and applied solutions of multi-mode adaptive intelligent data analysis for food industry enterprises have been developed. During the study of the methodological foundations of multi-mode adaptive intelligent data analysis, the effectiveness of using this analysis in the management of competitive food enterprises has been established. The main advantages, difficulties, challenges and problems of using the proposed analysis have been identified. A list of main corporate tasks has been formed, for the solution of which it is advisable to use this type of analysis. A list of main results of using this analysis for an effective and competitive food enterprise in dynamic and crisis conditions has been determined. During the study of scientific and applied solutions of multi-mode adaptive intelligent data analysis, the features, methods and main applied solutions of the following types of analysis have been determined: High Dimensional big data analysis, Ad-Hoc Data Mining, Anomaly & Fraud Detection, Hybrid Data Mining, Crisis Data Mining. The results of the study can be effective for enterprises and companies in which management decisions have been made in unstable or crisis conditions.

The third section analyzes the management aspects of the integration of Ukrainian railways into the international transport infrastructure. In the process of this analysis, the experience of planning and implementing high-speed railway projects in Europe, Asia and other regions has been studied. Particular attention has been paid to the adaptation of world practices to Ukrainian conditions, taking into account the specifics of the national infrastructure, economic and political factors. The features of the project for the integration of Ukrainian railways into the Trans-European Transport Network have been considered using the example of the Lviv railway junction. For this type of project, the stages of its implementation have been described, including technical, organizational and financial aspects, and an analysis of problems and achievements is conducted. The impact of this type of project on the development of regional infrastructure and the economy has been studied. Using the example of a project for the automatic identification of rolling stock and large-tonnage containers on Ukrainian railways, practical aspects of management processes, including planning, implementation, and monitoring of projects at the system level, have been explored. Examples of successful and problematic projects have been considered, illustrating the opportunities and challenges of the project management process in the context of Ukrainian railway transport.

The fourth section considers the application of the differential-symbolic approach to planning medical projects for supporting the population of communities. This approach involves the use of differential equations to describe the dynamics of projects as a separate system and the use of symbolic expressions to represent individual parameters and their description. Mathematical models for differential-symbolic planning of projects for improving the health of the population of communities and assessing the risks of projects for medical support of the population of communities have been developed. To implement the proposed models, code has been written in the Python programming language using libraries for solving differential equations, optimizing and visualizing results. Based on the use of the developed and implemented models for the given conditions of the project environment, the results of optimizing the configuration of projects for improving the health of the population in the community and assessing the risks of projects for medical support of the population of communities have been obtained.

The fifth section considers theoretical approaches, models and methods for assessing the quality of transportation projects as a means of increasing the efficiency of providing transport services in cargo transportation projects of a project-oriented enterprise. An N-model for making an optimal decision regarding the importance of a set of criteria that determine the quality of transport services, taking into account expert information, has been developed. It allows determining the advantages of one criterion over another based on the theory of the importance of criteria, which can be applied in project process management. A model for ensuring the relationship between the quality indicators of cargo transportation projects and determining the attractiveness of international routes has been developed. The effectiveness of applying the developed methods and models at project-oriented enterprises in the transport industry has been proven by testing them at motor transport enterprises.

This monograph can be useful to researchers, teachers, postgraduate students and higher education students in the field of project management, as well as specialists in applied project management in various spheres of human activity.