A Multiagent System to Solve JSSP Using a Multi-Population Cultural Algorithm

  • Mohammad R. Raeesi N.
  • Ziad Kobti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7310)


In this article, a multiagent system is proposed to solve Job Shop Scheduling Problems. In the proposed system, a number of autonomous agents cooperate in a Multi-Population Cultural Algorithm (MP-CA) framework. The proposed multiagent system consists of a number of groups of agents called sub-populations. The agents in each sub-population are co-evolving using a local CA. The local CAs are working in parallel and communicating to each other to exchange their extracted knowledge. The knowledge is migrated in the form of structured belief which is defined as a statistical records of an agent or a group of agents. Experiments show that our method outperforms some existing methods by offering better solutions as well as a better convergence rate.


Multiagent System Mutation Operator Autonomous Agent Memetic Algorithm Hybrid Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohammad R. Raeesi N.
    • 1
  • Ziad Kobti
    • 1
  1. 1.School of Computer ScienceUniversity of WindsorWindsorCanada

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