Нейро-эволюционный подход к метамоделированию и оптимизации системы инвентаризационного учета

Тип проекта: методологический

Описание:

Существует острая производственная потребность в автоматизации метамоделирования. Проект использует успех нейроэволюционных подходов в поиске нейронной архитектуры и оптимизации гиперпараметров для изучения возможностей и совмещения искусственной нейронной сети и генетического алгоритма для автоматического метамоделирования систем управления учетом. Разработанный фреймворк основан на самых известных современных практиках и демонстрирует существенные вычислительные возможности в классическом метамоделировании, сформулированном в форме регрессионной проблемы.

Финансирование: VIAA scholarship for doctoral research, decision N.1.-50.3/3889, decision N.1.-50.3/2978

Инструменты анализа данных и искусственного интеллекта:

• Искусственные нейронные сети
• Поиск нейронной архитектуры
• Генетический алгоритм

Результаты

• Jackson, I. (2020) GitHub repository “metainventory” [online] Available at: https://github.com/Jackil1993/metainventory
• Jackson, I. and Tolujevs, J. (2018) The Discrete-Event Approach to Simulate Stochastic Multi-Product (Q, r) Inventory Control Systems. In: proceedings of the 28th International Conference on Information Modelling and Knowledge Bases (EJC-2018), June 4-8, 2018, Riga, Latvia. pp. 94-101 [indexed by Scopus].
• Jackson, I., Tolujevs, J. and Reggelin, T. (2018) The Combination of Discrete-Event Simulation and Genetic Algorithm for Solving the Stochastic Multi-Product Inventory Optimization Problem. Transport and Telecommunication Journal, 19(3), pp. 233-243 [indexed by Scopus, indexed by Web of Science].
• Jackson, I., Tolujevs, J., Lang, S. and Kegenbekov, Z. (2019) Metamodeling of Inventory-Control Simulations Based on a Multilayer Perceptron. Transport and Telecommunication Journal, 20(3), pp. 251-259 [indexed by Scopus, indexed by Web of Science].
• Jackson, I. and Tolujevs, J. (2018) A combination of simulation and genetic algorithm for solving a stochastic inventory optimization problem. In: proceedings of 11th International Doctoral Student Workshop on Logistics, June 19, 2018, Magdeburg, Germany, pp. 31-35.
• Jackson, I. and Tolujevs, J. (2018) Simulation-driven artificial intelligence for solving stochastic combinatorial optimization problems in production and logistics. In: proceedings of PhD seminar Sci-Bi: Digitalization in Logistics and Transport, Riga, Latvia, pp. 30-36
• Jackson, I. and Tolujevs, J. (2019) Metamodeling of Inventory-Control Systems Based on Artificial Neural Networks. In: proceedings of 12th International Doctoral Student Workshop on Logistics, June 6, 2019, Magdeburg, Germany, pp. 82-86.
• Jackson, I. (2019) Simulation-Optimization Approach to Stochastic Inventory Control with Perishability. Information Technology & Management Science, 22, pp. 9-14.
• Jackson, I. (2019) Combining Simulation with Genetic Algorithm for Solving Stochastic Multi-Product Inventory Optimization Problem. The Journal of Economic Research & Business Administration, 130(4), pp. 96-102.
• Jackson, I. (2019) Neuroevolutionary Approach to Metamodeling of Production-Inventory Systems with Lost-Sales and Markovian Demand. In: proceedings of International Conference on Reliability and Statistics in Transportation and Communication. Springer, Cham, pp. 90-99 [indexed by Scopus].
• Jackson, I., Tolujevs, J. and Kegenbekov, Z. (2020) Review of Inventory Control Models: A Classification Based on Methods of Obtaining Optimal Control Parameters. Transport and Telecommunication Journal, 21(3), pp. 191-202 [Scopus, Web of Science].