Land Combat Scenario Planning: A Multiobjective Approach

  • Ang Yang
  • Hussein A. Abbass
  • Ruhul Sarker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)


The simulation of land combat operations is a complex task. The space of possibilities is exponential and the performance criteria are usually in conflict; thus finding a sweet spot in this complex search space is a hard task. This paper focuses on the effect of population size and mutation rate on the performance of NSGA–II, as the evolutionary multiobjective optimization technique, to decide on the composition of forces using a complex land combat multi-agent scenario planning tool.


Mutation Rate Objective Space Mutation Probability Multiobjective Approach Pareto Archive Evolution Strategy 
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 2006

Authors and Affiliations

  • Ang Yang
    • 1
  • Hussein A. Abbass
    • 1
  • Ruhul Sarker
    • 1
  1. 1.Defence and Security Applications Research Centre (DSA)University of New South Wales, Australian Defence Force AcademyCanberraAustralia

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