title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ¹ Ð´Ð»Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ°Ð±Ð¾ÑÑ ÑÐºÐ»Ð°Ð´ÑÐºÐ¸Ñ ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¸ ÑÐ¸ÑÑÐ¾Ð²ÑÑ Ð´Ð²Ð¾Ð¹Ð½Ð¸ÐºÐ¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Application of neural networks to optimize the operation of warehouse complexes based on digital twin technology
Creators: name: ÐÐ¾ÑÐ¾ÑÐµÐµÐ², ÐÑÑÐµÐ¼
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐ°ÑÐµÐ¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
Ð¡ÐºÐ»Ð°Ð´Ñ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼
Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ñ
reinforcement learning
optimization

description: ÐÂ Ð´Ð°Ð½Ð½Ð¾Ð¹Â ÑÐ°Ð±Ð¾ÑÐµÂ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½ÑÂ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµÂ ÑÐºÐ»Ð°Ð´Ñ,Â ÐºÐ°ÐºÂ ÑÐ°ÑÑÑ Ð»Ð¾Ð³Ð¸ÑÑÐ¸ÑÐµÑÐºÐ¾Ð¹Â ÑÐ¸ÑÑÐµÐ¼Ñ, Ð¾Ð¿Ð¸ÑÐ°Ð½ÑÂ ÐºÐ»ÑÑÐµÐ²ÑÐµÂ Ð¼ÐµÑÑÐ¸ÐºÐ¸Â ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¸ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸ÑÂ Ð´Ð»Ñ Ð¸Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸. ÐÑÐ±ÑÐ°Ð½Ð° ÑÑÐµÐ´Ð°Â Ð´Ð»ÑÂ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸. ÐÐ¿Ð¸ÑÐ°Ð½Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹, Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ Ðº Ð¸Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð²ÑÐ±ÑÐ°Ð½ Ð¼ÐµÑÐ¾Ð´ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð Ð°ÑÑÑÐ¸ÑÐ°Ð½Ñ ÑÐµÑÐ½Ð¸ÐºÐ¾-ÑÐºÑÐ¿Ð»ÑÐ°ÑÐ°ÑÐ¸Ð¾Ð½Ð½ÑÐµ Ð¿Ð¾ÐºÐ°Ð·Ð°ÑÐµÐ»Ð¸, Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼ÑÐµ Ð²Â ÐºÐ°ÑÐµÑÑÐ²ÐµÂ Ð¸ÑÑÐ¾Ð´Ð½ÑÑÂ Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»ÑÂ ÑÐ°Ð±Ð¾ÑÑ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹Â Ð¼Ð¾Ð´ÐµÐ»Ð¸. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Â Ð·Ð°Ð¿Ð¾Ð»Ð½ÐµÐ½Ð¸ÑÂ Ð²ÑÐ¾Ð´ÑÑÐ¸ÑÂ Ð¸ Ð¸ÑÑÐ¾Ð´ÑÑÐ¸Ñ Ð³ÑÑÐ·Ð¾Ð¿Ð¾ÑÐ¾ÐºÐ¾Ð². ÐÑÐ±ÑÐ°Ð½Ð° Ð±Ð°Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ, Ð´Ð»Ñ ÑÐ°Ð±Ð¾ÑÑ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸.Â Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð°Â Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð°ÑÂ Ð¼Ð¾Ð´ÐµÐ»ÑÂ ÑÐºÐ»Ð°Ð´ÑÐºÐ¾Ð³Ð¾Â ÐºÐ¾Ð¼Ð¿Ð»ÐµÐºÑÐ°. ÐÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¾Â Ð¼ÐµÑÑÐ¾Â Ð´ÐµÐ¹ÑÑÐ²Ð¸ÑÂ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹Â ÑÐµÑÐ¸Â Ð²Â Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹Â Ð¼Ð¾Ð´ÐµÐ»Ð¸, Ð¿ÐµÑÐµÐ´Ð°Ð²Ð°ÐµÐ¼ÑÐµ Ð½Ð°Ð±Ð»ÑÐ´ÐµÐ½Ð¸Ñ,Â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð°Â ÑÐ¸ÑÑÐµÐ¼Ð°Â Ð¾ÑÐµÐ½Ð¸Ð²Ð°Ð½Ð¸ÑÂ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². ÐÐ±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½ Ð²ÑÐ±Ð¾Ñ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¸ Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, Ð¾Ð¿Ð¸ÑÐ°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸Â Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ.Â ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½Ñ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÑÂ Ð±Ð°Ð·Ð¾Ð²Ð¾Ð³Ð¾Â Ð¸ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ ÑÑÐµÐ½Ð°ÑÐ¸ÐµÐ². ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð»ÑÑÐ¸Ð²ÑÐ¸ÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð², ÑÐ´ÐµÐ»Ð°Ð½ Ð²ÑÐ²Ð¾Ð´ Ð¾ ÑÐ°Ð±Ð¾ÑÐ¾ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð¾ÑÑÐ¸ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¸, Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ñ Ð¿Ð¾Ð»Ð¾Ð¶Ð¸ÑÐµÐ»ÑÐ½ÑÐµ ÑÑÑÐµÐºÑÑ.
description: ThisÂ paper presentsÂ modernÂ warehousesÂ asÂ partÂ ofÂ theÂ logisticsÂ system, describesÂ keyÂ performance metricsÂ andÂ directionsÂ for their optimization.Â The environmentÂ forÂ developingÂ theÂ simulationÂ model has beenÂ selected.Â The classifications of neural networks, approaches to their training are described, and the training method chosen. The technical and operational indicators required as input data for the operation of the simulation model are calculated. An algorithm for filling incoming and outgoing cargo flows has been developed. A database has been selected for the simulation model to operate. A simulation model of a warehouse complex has been developed. The place of action of the neural network in the simulation model was determined, the transmitted observations were determined, and a system for evaluating the results was developed. The choice of library for training a neural network is justified, and the algorithm for the training sequence is described. Experiments were carried out with basic and neural network-optimized scenarios. An analysis of the results was carried out, a conclusion was made about the efficiency of the technology, and positive effects were identified.