Wasp swarm optimization of logistic systems

  • Pedro Pinto
  • Thomas A. Runkler
  • João M. Sousa


In this paper, we present the optimization of logistic processes in supply chains using the meta-heuristic algorithm known as wasp swarm, which draws parallels between the process to optimize and the way individuals in wasp colonies interact and allocate tasks to meet the demands of the nest.


Supply Chain Random Search Logistic Process Birth Process Polistes Wasp 
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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8 References

  1. [1]
    R. Palm and T. A. Runkler (2002) Multi-agent control of queuing processes. IFAC World Congress, Barcelona, Spain.Google Scholar
  2. [2]
    G. Theraulaz, S. Goss, J. Gervet, and J. L. Deneubourg (1991) Task differentiation in polistes wasps colonies: A model for self-organizing groups of robots. From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior. MIT Press, pp. 346–355Google Scholar
  3. [3]
    V. A. Cicirello, and S. F. Smith (2004) Wasp-Like Agents for Distributed Factory Coordination Agents. Autonomous Agents and Multi-agent systems 8: 237–266CrossRefGoogle Scholar
  4. [4]
    M. Dorigo and V. Maniezzo and A. Colorni (1996) Ant System: Optimization by a colony of cooperating agents. EEE Transactions on Systems, Man, and Cybernetics-Part B 26(1): 29–41CrossRefGoogle Scholar
  5. [5]
    C. A. Silva and T. A. Runkler and J. M. Sousa and R. Palm (2002) Ant Colonies as Logistic Process Optimizers. Ant Algorithms, International Workshop ANTS 2002, Brussels, Belgium. Springer, pp. 76–87Google Scholar
  6. [6]
    C. A. Silva and J. M. Sousa and R. Palm and T. A. Runkler (2002) Optimization of Logistic Processes Using Ant Colonies. Workshop Agent Based Simulation pp. 143–148Google Scholar
  7. [7]
    C. A. Silva and T. A. Runkler and J. M. Sousa and J. M. Sá da Costa (2003) optimization of Logistic Processes in Supply—Chains using Meta—Heuristics. LNAI 2902, Progress in Artificial Intelligence, 11th Portuguese Conference on Artificial Intelligence, Beja, Portugal. Springer Verlag pp 9–23Google Scholar
  8. [8]
    R. W. Wolff (1989) Stochastic Modeling and the Theory of Queues. Prentice-HallGoogle Scholar

Copyright information

© Springer-Verlag/Wien 2005

Authors and Affiliations

  • Pedro Pinto
    • 1
    • 2
  • Thomas A. Runkler
    • 1
  • João M. Sousa
    • 2
  1. 1.Information and Communications, CT IC 4Siemens AG, Corporate TechnologyMunichGermany
  2. 2.Instituto Superior Técnico, Dep. Mechanical Engineering - Control, Automation and Robotics GroupTechnical University of LisbonLisbonPortugal

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