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ABSTRACT

The predator-prey model--based on aspects of the natural interplay of predators and prey--has become an alternative method for tackling multi-objective optimization problems. In this process, each predator targets a single objective, and it is expected that the joint influence of all predators affects the prey population in such a way that good solutions survive. This paper describes PEPPA, a modular software framework for designing and analyzing predator-prey models. It allows to model arbitrary world environments, complex predator behavior and dynamic prey adaptation. Further, PEPPA provides various tools for modeling, visualization and parallelization. We explain the architecture and handling of the framework and provide exemplary results on a simple multi-objective benchmark problem.

REFERENCES

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• 4: Kalyanmoy Deb , Samir Agrawal , Amrit Pratap , T. Meyarivan, A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II, Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, p.849-858, September 18-20, 2000
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INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
        D.2.11 Software Architectures
            Subjects: Domain-specific architectures

Additional Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.5 Model Development
          Subjects: Modeling methodologies

General Terms:
Algorithms, Design, Experimentation

Keywords:
evolutionary algorithms, framework, multi-objective optimization, objectoriented programming