Self-Organization through a multi-agent system for orders distribution in large companies

  • Alberto Montero
    University of Salamanca id00714676[at]
  • Sergio Rodríguez
    University of Salamanca
  • Felipe Sánchez
    University of Salamanca
  • Alberto Yébenes
    University of Salamanca


This article presents the development of a multi-agent system in charge of self-managing a delivery system. The article focuses on the delivery management system and not on the movement systems of the different used vehicles.This system consists of different types of vehicles, each with different characteristics, and there may be several instances of each type of vehicle. There will be three operating agents (Drone Operator, Car Operator and Amphibious Operator), an agent that will be responsible for creating random tasks (used only in simulations) and another one that is responsible for distributing these tasks to the operators taking into account the algorithm. This algorithm follows the bases of backtracking and its main function is to assign a task to a vehicle taking into account the distance, the consumption, the limitations of weight and distances, etc. The whole system has been developed in JADE on java. The described software performs a complete simulation with a console in which it is indicated relevant information such as the tasks that are created, the type of vehicle and the instance of that type of vehicle that resolve the delivery, among others. The purpose of this system is to minimize costs and times.
  • Referencias
  • Cómo citar
  • Del mismo autor
  • Métricas
Bechlioulis, C., Rovithakis, G. A., 2016. Decentralized Robust Synchronization of Unknown High Order Nonlinear Multi-Agent Systems with Prescribed Transient and Steady State Performance. Pages 123-134. IEEE -

Briones, C. D., Machaen, Z. A., Martín, L. M., Torres, G. A., 2018. Self-organizing mobile robots based on multi-agent coordination techniques implemented with aerial vision and communication gateway between Wi-Fi and RF.

Castelfranchis, C., 1997. Modeling social interaction for Al agents. Pages 1567-1576.

Castelfranchis, C., Dignum, F., Jonker, C., Treur, J., 1999. Deliberative normative agents: Principles and architecture. Pages 364-378. Springer, Berlin, Heidelberg. -

Chamoso, P., De la Prieta, F., Bajo, J., Corchado, J. M., 2019. Conflict resolution with agents in smart cities. Pages 695-713. IGI Global. -

Corchado, J. M., Bajo, J., De Paz, Y., Tapia, D., 2008. Intelligent environment for monitoring Alzheimer patients, agent technology for health care. Pages 382-396. North-Holland. -

Corchado, J. M., Lasa, R., 2003. Constructing deliberative agents with case-based reasoning technolgy. Pages 1227-1241. Wiley Subscription Services, Inc., A Wiley Company. -

Corchado, J.M., Lees, B., 2001. A hybrid case-based model for forecasting. Pages 106-127- Applies Artificial Intelligence. -

Dimopoulos, Y., Moraitis, P., 2006. Multi-agent coordination and cooperation through classical planning. Pages 398-402. IEEE/WIC/ACM. -

Fyfe, C., Corchado, E., González, M., Corchado, J.M., 2002. Analytical Model for Constructing Deliberative Agents. CRL Publishing.

Guo, G., Ding, L., Han, Q., 2014. A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems. Pages 1489-1496. Pergamon. -

Jennings, N.R., Wooldridge, M., 1998. A roadmap of agent research and development. Pages 7-38. Springer Netherlands.

Jennings, N.R., 2000. On agent-based software engineering. Pages 117. Elseiver. -

Jennings, N.R., Wooldridge, M., Kinny, D, 2000. The Gaia methodology for agent-oriented analysis and design. Pages 284-312. Springer Netherlands. -

Jennings, N.R., Wooldridge, M., 1994. Agent theories, architectures and languages: a survey. Pages 1-39. Springer, Berlin, Heidelberg. -

Muñoz, R., Aguirre, R., García-Silvente, M., Gomez, M., 2005. A multi-agent system architecture for mobile robot navigation based on fuzzy and visual behavior. Pages 689-699. -

Pelrine, R., Hsu, A., Cowan, C., Wong-Foy, A., 2017. Multi-agent systems using diamagnetic micro manipulation - From floating swarms to mobile sensors. IEEE. -

Peng, Z., Wen, G., Rahmani, A., 2013. Leader-follower formation control of multiple nonholonomic robots based on backstepping. Pages 211-216. ACM. -

Román, J. A., Rodríguez, S., 2016. Improvement in the distribution of services in multi-agent systems with SCODA. Pages 31-46, v. 4, n. 3. ADCAIJ -

Shouwenaats, T., De Moor, B., Feron, E., How, J., 2001. Mized integer programming for multi-vehicle path planning. Pages 2603-2608. IEEE. -

Turner, J. R., 2013. Multiagent systems as a team member. Pages 73-90. International Journal of Technology, Knowledge & Society, vol. 9, no. 1. -

Wooldridge, M., 1997. Agent-based software engineering. Pages 26-37. IET. -

Wooldridge. M., 2009. An introduction to multiagent systems.
Montero, A., Rodríguez, S., Sánchez, F., & Yébenes, A. (2018). Self-Organization through a multi-agent system for orders distribution in large companies. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 7(4), 65–71.


Download data is not yet available.