Cargo Transportation Models Analysis using Multi-Agent Adaptive Real-Time Truck Scheduling System

Oleg Granichin, Petr Skobelev, Alexander Lada, Igor Mayorov, Alexander Tsarev

Abstract

The use of multi-agent platform for real-time adaptive scheduling of trucks is considered. The schedule in such system is formed dynamically by balancing the interests of orders and resource agents. The system doesn’t stop or restart to rebuild the plan of mobile resources in response to upcoming events but finds out conflicts and adaptively re-schedule demand-resource links in plans when required. Different organizational models of cargo transportation for truck companies having own fleet are analyzed based on simulation of statistically representative flows of orders. Models include the rigid ones, where trucks return back to their garage after each trip, and more flexible, where trucks wait for new orders at the unloading positions, where trucks can be late but pay a penalty for this, and finally where orders can be adaptively rescheduled ’on the fly‘ in real-time and the schedule of each truck can change individually during orders execution. Results of simulations of trucks profit depending on time period are presented for each model. These results show measurable benefits of using the multi-agent systems with real-time decision making - up to 40-60% comparing with rigid models. The profit dependencies on the number of trucks are also built and analyzed. The results show that using adaptive scheduling in real time it is possible to execute the same number of orders with less trucks (up to 20%).

References

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Paper Citation


in Harvard Style

Granichin O., Skobelev P., Lada A., Mayorov I. and Tsarev A. (2013). Cargo Transportation Models Analysis using Multi-Agent Adaptive Real-Time Truck Scheduling System . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8565-39-6, pages 244-249. DOI: 10.5220/0004225502440249


in Bibtex Style

@conference{icaart13,
author={Oleg Granichin and Petr Skobelev and Alexander Lada and Igor Mayorov and Alexander Tsarev},
title={Cargo Transportation Models Analysis using Multi-Agent Adaptive Real-Time Truck Scheduling System},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2013},
pages={244-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004225502440249},
isbn={978-989-8565-39-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Cargo Transportation Models Analysis using Multi-Agent Adaptive Real-Time Truck Scheduling System
SN - 978-989-8565-39-6
AU - Granichin O.
AU - Skobelev P.
AU - Lada A.
AU - Mayorov I.
AU - Tsarev A.
PY - 2013
SP - 244
EP - 249
DO - 10.5220/0004225502440249