Neiro-evolucionāra pieeja meta modelēšanai un krājumu kontroles sistēmu optimizēšanai

Periods: 01.01.2018
- 01.01.2020

Projekta uzraugi:

Docents 

Dr. sc. ing.
Ilya Jackson
Inženierzinātņu fakultāte
Ilya Jackson

Academic degree and current position in TSI: assistant professor, researcher at the research cluster “Data Analytics and Artificial Intelligence

Previous experience: 4 years of lecturing and research at the Transport and Telecommunication Institute (TSI)

Membership: Reviewer of the Hawaii International Conference on System Sciences (HICSS) and Transport Journal. Member of the scientific committee of the International Scientific Conference “Transbaltica 2021”. Member of a working group European Transport Research Review (ECTRI), thematic group “freight & logistics”.

Academic experience: More than 13 publications indexed by SCOPUS and WoS. Author of such courses as “Risk management in supply chains”, “Modeling Logistic and transport processes”, “Logistic systems and chains”.

Teaching at post- and graduate level: Risk management in supply chains (MSc in Transport and Logistics), Modeling Logistic and transport processes (MSc in Transport and Logistics), Logistic systems and chains (MSc in Transport and Logistics).

Participation in projects: participated as a researcher in several European projects including ALLIANCE (ID: 692426) and ePIcenter (ID: 861584).

Research Interests: Supply chain management, applied machine learning, simulation modelling, operations research and metaheuristics.

Supervised Doctoral, Master and Bachelor Theses (number): 1 master student completed master’s degree under my supervision.

Awards: Young Researcher Award was received at the 20th International Multi-Conference Reliability and Statistics in Transportation and Communication, 2020, Riga, Latvia. Awarded paper: “Neuroevolutionary approach to metamodel-based optimization in production and logistics”

Projekta tips: Metodiskais

Galvenais izaicinājums:

Ņemot vērā steidzamo rūpniecisko vajadzību metamodelēšanas automatizācijā un nesenos neiroevolūcijas pieeju panākumus neironu arhitektūras meklēšanā un hiperparametru optimizācijā, tā mērķis ir pārbaudīt mākslīgā neironu tīkla un ģenētiskā algoritma kombinācijas iespējamību un efektivitāti krājumu kontroles sistēmu automatizētai metamodelēšanai. Izstrādātais ietvars ir balstīts uz visizcilāko modernāko praksi, un tas parāda stabilas skaitļošanas iespējas klasiskajā metamodelēšanā, kas formulēts kā regresijas problēma. Turklāt reālās situācijas izpētē tiek apspriesta iespēja izmantot piedāvāto sistēmu optimālu kontroles parametru iegūšanai.

Finansējums: VIAA stipendija doktora studijām, lēmums N.1. -50,3/3889, lēmums N.1. -50,3/2978.

DA&AI rīki:

  • Mākslīgie neironu tīkli
  • Neironu arhitektūras meklēšana
  • Ģenētiskais algoritms

Rezultāti (publikācijas, ziņojumi, apliecinājumi utt.)

  • 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].

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