A Mixed Neuro Graph Approach with Gradient Boosting to Hybrid Job-Shop Scheduling to Minimize a Regular Function of Job Completion Times and Numbers of Used Machines

Sotskov Y. Mikhaylov A. Mutaliyeva L. Stepanova D. Chang T. Barykin S. Zadehbagheri M.
2024 Universal Wiser Publisher

Contemporary Mathematics (Singapore)
2024 #5 Issue 4 5168 - 5177 pp.

The paper considers a multi-stage processing system including sets of identical (parallel) machines and a set of dedicated machines processing different operations of the given jobs in any sectors of economy. Based on the weighted Mixed Neuro graph model, the paper proposes adaptive algorithms for solving this problem via appropriate Mixed Neuro graph transformations. The main novelty is (1) low demands on the source data-unlike classical machine learning algorithms, the approach can offer stable interpretable results even with a short dataset size; (2) the number of new matrix multiplication operations that make up the main load when training models increases linearly with the number of new data from 0 to 999 time periods; (3) the results of the model are repeatable due to the stability of the coefficients of the model. These algorithms are able to solve (exactly or heuristically) the tested instances with N jobs and W types of parallel identical machines within on the personal computer. The gradient boosting result is in interval 5.9677410-3.4982093.

adaptive algorithm , flexible job-shop , regular objective function , scheduling

Text of the article Перейти на текст статьи

Financial Faculty, Financial University under the Government of the Russian Federation, Moscow, Russian Federation
L.N. Gumilyov Eurasian National University, Nur-Sultan, Kazakhstan
Department of Prices, Plekhanov Russian University of Economics, Moscow, Russian Federation
Department of Finance, Feng Chia University, Taichung, Taiwan
Departmenf of Financial Logistics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russian Federation
Department of Electrical Engineering, Yasuj Branch, Islamic Azad University, Yasuj, Iran
Scientific Department, Western Caspian University, Baku, Azerbaijan
Scientific Department, Baku Eurasian University, Baku, Azerbaijan

Financial Faculty
L.N. Gumilyov Eurasian National University
Department of Prices
Department of Finance
Departmenf of Financial Logistics
Department of Electrical Engineering
Scientific Department
Scientific Department

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026