DC Field | Value | Language |
dc.contributor.author | Alooeff, E. | - |
dc.contributor.author | Adzinets, D. | - |
dc.coverage.spatial | Cracow | en_US |
dc.date.accessioned | 2024-06-25T12:23:59Z | - |
dc.date.available | 2024-06-25T12:23:59Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Alooeff, E. Multi-agent system for intelligent scheduling / E. Alooeff, D. Adzinets // Communications of the ECMS : proceedings of the 38th ECMS International Conference on Modelling and Simulation, Cracow, Poland, June 4th – June 7th, 2024 / Cracow University of Technology ; ed.: D. Grzonka [et al.]. – Cracow, 2024. – Vol. 38, Iss. 1. – P. 507–512. | en_US |
dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/56200 | - |
dc.description.abstract | This work is dedicated to the development of a multiagent system for intelligent scheduling: to simulate, to analyze and to optimize used parameters to achieve the best performance in terms of increasing the speed of Technician agents (they provide a field service), reducing transport and time costs for their movement to Service Appointment agents (they are waiting for the Technician agent’s active interaction) and Dispatcher agents (they analyze and distribute the relations between another agents. Nowadays the most of the current scheduling models on the market are centralized. This paper exposes a way to use a multi agent-based
approach to shift the scheduling system from centralized control to decentralized decisions made by agents. The implemented model allows us to check the model of dynamic scheduling with the real data under a real-time environment and it allows us to test interactions between the agents of three different types. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Cracow University of Technology | en_US |
dc.subject | публикации ученых | en_US |
dc.subject | model | en_US |
dc.subject | agent | en_US |
dc.subject | multi-agent system | en_US |
dc.subject | dynamic scheduling | en_US |
dc.subject | optimization | en_US |
dc.title | Multi-agent system for intelligent scheduling | en_US |
dc.type | Article | en_US |
Appears in Collections: | Публикации в зарубежных изданиях
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