Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110856 - 110856

Опубликована: Янв. 1, 2025

Язык: Английский

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Exploring multi-agent reinforcement learning for unrelated parallel machine scheduling

The Journal of Supercomputing, Год журнала: 2025, Номер 81(4)

Опубликована: Фев. 19, 2025

Язык: Английский

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Simulation Model as an Element of Sustainable Autonomous Mobile Robot Fleet Management

Energies, Год журнала: 2025, Номер 18(8), С. 1894 - 1894

Опубликована: Апрель 8, 2025

Computer simulations of processes are increasingly used in business practice to improve the results an enterprise and maximise its value. Designing process models simulating their behaviour provide opportunity analyse economic operational before appropriate organisational, location, investment decisions made. This article presents possibilities using simulation modelling intralogistics systems. In presented article, a decision-making support tool based on DES simulator developed by authors was proposed. supports analysis parameters that affect energy efficiency analysed sustainability. The proposed were giving example implementation automation processes. As part implementation, use Autonomous Mobile Robot (AMR) vehicles By conducting experiments system model analysing obtained also terms consumption AMR vehicles, project can be verified improvements this research confirmed possibility for supporting assessing designed system. method is cost-free element helps management staff given make decisions.

Язык: Английский

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An evolution strategies-based reinforcement learning algorithm for multi-objective dynamic parallel machine scheduling problems

Swarm and Evolutionary Computation, Год журнала: 2025, Номер 95, С. 101944 - 101944

Опубликована: Апрель 18, 2025

Язык: Английский

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