PEPPA: a project for evolutionary predator prey algorithms

Authors:
Hendrik Blom;Christiane Küch;Katja Losemann;Chris Schwiegelshohn
Affiliations:
TU Dortmund University, Dortmund, Germany;TU Dortmund University, Dortmund, Germany;TU Dortmund University, Dortmund, Germany;TU Dortmund University, Dortmund, Germany
Venue:
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Year:
2009

Citing 5
Cited 0

Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
A Spatial Predator-Prey Approach to Multi-objective Optimization: A Preliminary Study

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A real-coded predator-prey genetic algorithm for multiobjective optimization

EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Designing multi-objective variation operators using a predator-prey approach

EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Quantifying the effects of objective space dimension in evolutionary multiobjective optimization

EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization

Quantified Score

Hi-index	0.00

Visualization

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.