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• MODEL AND ALGORITHM OF OPERATIONAL PLANNING OF LOGISTIC PROCESSES OF TIMELY DELIVERY OF CARGO WITH THE INTERACTION OF A GROUP OF ROBOTIC COMPLEXES

  Е.D. Grigoreva, V.А. Ushakov

  2025-04-27

  Abstract ▼

  The purpose of the study is to improve the quality of operational planning (program control) of logistics
  processes in the conditions of modern urban systems with the interaction of a group of robotic systems.
  The quality of management in this study will be assessed by the number of deliveries completed after
  established directive deadlines. The goal set during the study is decomposed into the following tasks: system
  analysis of the current state of research in the field of metropolitan logistics, implementation of a
  substantive and formal formulation of the problem of operational planning of logistics processes in a metropolis
  using a group of robotic complexes, development of a model and algorithm for operational planning
  of logistics processes in a metropolis using a grouping of robotic complexes, development of special
  model-algorithmic support and its software prototype for solving the problem of operational planning of
  logistics processes in a metropolis using a grouping of robotic complexes. Proactive (anticipatory) management
  of a group of robotic systems when solving transport and logistics problems in a metropolis within the framework of the “Smart City” concept allows increasing the economic efficiency of cargo delivery.
  The article examines the scientific and technical problem of synthesizing technologies (plans) for the timely
  delivery of small-sized cargo using a group of robotic systems. The scientific significance lies in the
  application of the concept of integrated (system) modeling and proactive (anticipatory) management, and
  the practical significance lies in ensuring timely delivery of goods using a group of robotic complexes in a
  metropolis. The article discusses an example of solving the problem of operational planning of logistics
  processes using the example of Innopolis using the characteristics of Yandex delivery robots (as robotic
  complexes). During the study, an analysis of various options for objective functions was carried out: maximizing
  profit and minimizing delivery time; profit maximization; minimizing time; minimizing the number
  of robotic systems. The following indicators were chosen to evaluate the results obtained: total profit from
  deliveries; the number of deliveries not delivered on time and the total number of completed orders.
  The most suitable objective functions for solving the problem are time minimization or simultaneous time
  minimization and profit maximization. In addition, the conclusion provides directions for further research

• MULTI-AGENT INTELLIGENT SYSTEM FOR CONTROL OF PARKING SPACES IN CITY INFRASTRUCTURE

  I. А. Pshenokova, К.C. Bzhikhatlov, М.А. Kanokova

  2025-04-27

  Abstract ▼

  With the growing number of cars and limited space, many cities are realizing the importance of implementing
  intelligent parking systems to improve urban mobility and convenience for drivers. The level of
  implementation of intelligent parking based on various technological solutions is growing, but to achieve
  maximum efficiency, it is necessary to continue to develop technologies, integrate them with other systems
  and take into account the needs of users. The purpose of the study is to develop a multi-agent intelligent
  system for monitoring and managing parking space reservations in the city parking network. The architecture
  of a multi-agent intelligent parking management system has been developed, which provides automatic
  access control to parking spaces taking into account the wishes of parking lot owners, driver orders, the traffic
  situation in the city and safety requirements. The main element of the developed system is parking, which
  is represented by a set of parking spaces equipped with automated parking space management systems (parking
  attendants), a communication system and data collection tools (surveillance camera and weather stations).
  Parking spaces and parking attendants are managed by an intelligent control system based on multiagent
  neurocognitive architectures. A prototype of a hardware and software complex of a multi-agent intelligent
  parking space management system has been developed in the form of a client-server architecture.
  The server is responsible for collecting, processing, storing data and managing automated parking attendants.
  Two types of clients are connected to the server - a mobile application of the administrator and the
  driver. The administrator has the ability to manage parking (set fixed prices or use server recommendations,
  book parking spaces for employees) and view statistics (current load, parking statistics, data on accepted
  payments, parking work forecast, recommendations). The driver has the ability to view the status of parking
  in the area of interest (number of free spaces, waiting time for a free space, cost, recommendations for the
  most convenient parking) and book a parking space with the ability to pay online